it job board logo
  • Home
  • Find IT Jobs
  • Register CV
  • Register as Employer
  • Contact us
  • Career Advice
  • Recruiting? Post a job
  • Sign in
  • Sign up
  • Home
  • Find IT Jobs
  • Register CV
  • Register as Employer
  • Contact us
  • Career Advice
Sorry, that job is no longer available. Here are some results that may be similar to the job you were looking for.

81 jobs found

Email me jobs like this
Refine Search
Current Search
machine learning operations engineer
Data Engineer/Data Architect
Vaco LLC Hollywood, Florida
Senior Data Engineer / Data Architect Location: Fort Lauderdale, FL Work Arrangement: Fully onsite Employment Type: Direct hire, full-time Role Type: Hands-on individual contributor and technical lead Position Overview We are seeking a Senior Data Engineer / Data Architect to lead the design and hands-on development of our enterprise data foundation. This role will connect data across ERP, CRM, ecommerce, marketing, production, finance, fulfillment, and internal business systems to support trusted reporting, AI initiatives, automation, and internal applications. This is not an architecture-only or advisory position. The successful candidate must have genuine architecture experience and the ability to personally build production-grade data platforms, pipelines, models, integrations, quality controls, and data services from the ground up. The ideal candidate combines strong engineering execution with the ability to define scalable architecture, establish technical standards, and communicate effectively with both technical and business stakeholders. Top Requirements Hands-on experience with Databricks, including Lakehouse architecture, Apache Spark, data pipelines, notebooks, workflows, and production deployments. True data architecture experience, including designing enterprise data platforms, defining systems of record, developing data models, establishing data governance, and making cross-system architecture decisions. Demonstrated success engineering implementations from the ground up, rather than only maintaining or advising on existing solutions. Key Responsibilities Data Architecture Assess the current data environment, including systems, databases, APIs, integrations, reports, scheduled jobs, and data owners. Design and implement a scalable enterprise data architecture supporting reporting, AI, analytics, and internal applications. Define authoritative systems of record for customer, product, order, revenue, inventory, location, marketing, and production data. Establish common data models, identifiers, data contracts, schema standards, retention policies, and integration patterns. Determine appropriate use of batch processing, real-time events, APIs, webhooks, and governed data services. Develop architecture diagrams, technical standards, roadmaps, and implementation plans. Data Engineering and Implementation Build production-grade data pipelines and lakehouse solutions in Databricks. Develop reliable ETL and ELT processes using SQL, Python, Apache Spark, and orchestration tools. Integrate data from ERP, CRM, ecommerce, marketing, manufacturing, finance, and internal applications. Create tested transformations that produce consistent and reusable business data. Build secure APIs and data services for approved reporting, AI, automation, and application use cases. Design systems that handle failures, changing schemas, retries, late-arriving data, and duplicate-processing risks. Establish source control, automated testing, code review, deployment pipelines, and release processes for data engineering work. Data Quality and Reliability Implement automated checks for completeness, accuracy, freshness, duplication, volume changes, and consistency. Reconcile key business measures such as orders, revenue, inventory, customer counts, and production activity across systems. Monitor pipeline performance, failed jobs, delayed data, schema changes, and data-quality incidents. Build alerting, operational dashboards, runbooks, and incident-response processes. Work with source-system owners to correct the root causes of data issues. Governance, Security, and Documentation Establish practical standards for data ownership, classification, access, retention, and approved use. Apply role-based access controls, encryption, audit logging, and appropriate protection for sensitive and confidential information. Maintain clear data definitions, lineage, integration documentation, runbooks, and architecture diagrams. Partner with IT, Legal, Infrastructure, Applications, and business leaders on privacy, security, and compliance requirements. Create governed access patterns that reduce uncontrolled direct access to production systems. Reporting, AI, and Internal Applications Develop trusted, reusable data models for reporting, dashboards, forecasting, and business analysis. Prepare structured and governed data for AI agents, retrieval systems, automations, machine learning, and internal applications. Partner with the Director of AI and internal product teams to accelerate delivery of data and AI use cases. Establish standards for monitoring how applications and AI solutions access and use company data. Cross-Functional Leadership Collaborate with technology, finance, operations, ecommerce, marketing, sales, production, and other business teams. Translate technical data risks into clear business impacts, options, costs, and recommended actions. Review vendor-built integrations for documentation, security, maintainability, and quality. Provide technical leadership and establish standards that improve how teams collect, define, share, and use data. Work independently, set priorities, document decisions, and deliver measurable results. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. EEO Notice Vaco by Highspring is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race (including but not limited to traits historically associated with race such as hair texture and hair style), color, sex (includes pregnancy or related conditions), religion or creed, national origin, citizenship, age, disability, status as a veteran, union membership, ethnicity, gender, gender identity, gender expression, sexual orientation, marital status, political affiliation, or any other protected characteristics as required by federal, state or local law. Vaco by Highspring and its parents, affiliates, and subsidiaries are committed to the full inclusion of all qualified individuals. As part of this commitment, Vaco by Highspring and its parents, affiliates, and subsidiaries will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact . Vaco by Highspring also wants all applicants to know their rights that workplace discrimination is illegal. Representation Notice By submitting to this position, you agree that you will be giving Vaco by Highspring the exclusive right to present your as a candidate for the foregoing employment opportunity. You further agree that you have represented information about yourself accurately and have not affirmatively misrepresented your qualifications. You also agree to maintain as confidential, to the fullest extent permitted by law, any information you learn from Vaco by Highspring about the position and you will limit disclosure of information about the position only to the extent necessary to perform any obligations in furtherance of your application. In exchange, Vaco by Highspring agrees to exercise reasonable efforts to represent you through all solicitation, job screening and resume dispersal. For residents of Ontario, Canada: Based on Highspring's discussions with its Client, Highspring's understanding is that this position for employment is a current vacancy (either through Highspring as a contractor or with the client directly). Privacy Notice Vaco by Highspring and its parents, affiliates, and subsidiaries ("we," "our," or "Vaco by Highspring") respects your privacy and are committed to providing transparent notice of our policies. California residents may access Vaco by Highspring HR Notice at Collection for California Applicants and Employees here. Virginia residents may access our state specific policies here. Residents of all other states may access our policies here. Canadian residents may access our policies in English here and in French here. Residents of countries governed by GDPR may access our policies here. Additionally, submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. More details about Vaco by Highspring's use of AI can be found here (). Further assessment of candidates beyond this initial phase will be conducted by recruiters and hiring managers. Vaco by Highspring does not know and cannot opine on if its client's use of AI products in hiring. Pay Transparency Notice Determining compensation for this role (and others) at Vaco by Highspring depends upon a wide array of factors including but not limited to: the individual's skill sets, experience and training; licensure and certification requirements; office location and other geographic considerations; other business and organizational needs. With that said, as required by local law, Vaco by Highspring believes that the following salary range referenced above reasonably estimates the base compensation for an individual hired into this position in geographies that require salary range disclosure. The individual may also be eligible for discretionary bonuses.
09/26/2026
Full time
Senior Data Engineer / Data Architect Location: Fort Lauderdale, FL Work Arrangement: Fully onsite Employment Type: Direct hire, full-time Role Type: Hands-on individual contributor and technical lead Position Overview We are seeking a Senior Data Engineer / Data Architect to lead the design and hands-on development of our enterprise data foundation. This role will connect data across ERP, CRM, ecommerce, marketing, production, finance, fulfillment, and internal business systems to support trusted reporting, AI initiatives, automation, and internal applications. This is not an architecture-only or advisory position. The successful candidate must have genuine architecture experience and the ability to personally build production-grade data platforms, pipelines, models, integrations, quality controls, and data services from the ground up. The ideal candidate combines strong engineering execution with the ability to define scalable architecture, establish technical standards, and communicate effectively with both technical and business stakeholders. Top Requirements Hands-on experience with Databricks, including Lakehouse architecture, Apache Spark, data pipelines, notebooks, workflows, and production deployments. True data architecture experience, including designing enterprise data platforms, defining systems of record, developing data models, establishing data governance, and making cross-system architecture decisions. Demonstrated success engineering implementations from the ground up, rather than only maintaining or advising on existing solutions. Key Responsibilities Data Architecture Assess the current data environment, including systems, databases, APIs, integrations, reports, scheduled jobs, and data owners. Design and implement a scalable enterprise data architecture supporting reporting, AI, analytics, and internal applications. Define authoritative systems of record for customer, product, order, revenue, inventory, location, marketing, and production data. Establish common data models, identifiers, data contracts, schema standards, retention policies, and integration patterns. Determine appropriate use of batch processing, real-time events, APIs, webhooks, and governed data services. Develop architecture diagrams, technical standards, roadmaps, and implementation plans. Data Engineering and Implementation Build production-grade data pipelines and lakehouse solutions in Databricks. Develop reliable ETL and ELT processes using SQL, Python, Apache Spark, and orchestration tools. Integrate data from ERP, CRM, ecommerce, marketing, manufacturing, finance, and internal applications. Create tested transformations that produce consistent and reusable business data. Build secure APIs and data services for approved reporting, AI, automation, and application use cases. Design systems that handle failures, changing schemas, retries, late-arriving data, and duplicate-processing risks. Establish source control, automated testing, code review, deployment pipelines, and release processes for data engineering work. Data Quality and Reliability Implement automated checks for completeness, accuracy, freshness, duplication, volume changes, and consistency. Reconcile key business measures such as orders, revenue, inventory, customer counts, and production activity across systems. Monitor pipeline performance, failed jobs, delayed data, schema changes, and data-quality incidents. Build alerting, operational dashboards, runbooks, and incident-response processes. Work with source-system owners to correct the root causes of data issues. Governance, Security, and Documentation Establish practical standards for data ownership, classification, access, retention, and approved use. Apply role-based access controls, encryption, audit logging, and appropriate protection for sensitive and confidential information. Maintain clear data definitions, lineage, integration documentation, runbooks, and architecture diagrams. Partner with IT, Legal, Infrastructure, Applications, and business leaders on privacy, security, and compliance requirements. Create governed access patterns that reduce uncontrolled direct access to production systems. Reporting, AI, and Internal Applications Develop trusted, reusable data models for reporting, dashboards, forecasting, and business analysis. Prepare structured and governed data for AI agents, retrieval systems, automations, machine learning, and internal applications. Partner with the Director of AI and internal product teams to accelerate delivery of data and AI use cases. Establish standards for monitoring how applications and AI solutions access and use company data. Cross-Functional Leadership Collaborate with technology, finance, operations, ecommerce, marketing, sales, production, and other business teams. Translate technical data risks into clear business impacts, options, costs, and recommended actions. Review vendor-built integrations for documentation, security, maintainability, and quality. Provide technical leadership and establish standards that improve how teams collect, define, share, and use data. Work independently, set priorities, document decisions, and deliver measurable results. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. EEO Notice Vaco by Highspring is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race (including but not limited to traits historically associated with race such as hair texture and hair style), color, sex (includes pregnancy or related conditions), religion or creed, national origin, citizenship, age, disability, status as a veteran, union membership, ethnicity, gender, gender identity, gender expression, sexual orientation, marital status, political affiliation, or any other protected characteristics as required by federal, state or local law. Vaco by Highspring and its parents, affiliates, and subsidiaries are committed to the full inclusion of all qualified individuals. As part of this commitment, Vaco by Highspring and its parents, affiliates, and subsidiaries will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact . Vaco by Highspring also wants all applicants to know their rights that workplace discrimination is illegal. Representation Notice By submitting to this position, you agree that you will be giving Vaco by Highspring the exclusive right to present your as a candidate for the foregoing employment opportunity. You further agree that you have represented information about yourself accurately and have not affirmatively misrepresented your qualifications. You also agree to maintain as confidential, to the fullest extent permitted by law, any information you learn from Vaco by Highspring about the position and you will limit disclosure of information about the position only to the extent necessary to perform any obligations in furtherance of your application. In exchange, Vaco by Highspring agrees to exercise reasonable efforts to represent you through all solicitation, job screening and resume dispersal. For residents of Ontario, Canada: Based on Highspring's discussions with its Client, Highspring's understanding is that this position for employment is a current vacancy (either through Highspring as a contractor or with the client directly). Privacy Notice Vaco by Highspring and its parents, affiliates, and subsidiaries ("we," "our," or "Vaco by Highspring") respects your privacy and are committed to providing transparent notice of our policies. California residents may access Vaco by Highspring HR Notice at Collection for California Applicants and Employees here. Virginia residents may access our state specific policies here. Residents of all other states may access our policies here. Canadian residents may access our policies in English here and in French here. Residents of countries governed by GDPR may access our policies here. Additionally, submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. More details about Vaco by Highspring's use of AI can be found here (). Further assessment of candidates beyond this initial phase will be conducted by recruiters and hiring managers. Vaco by Highspring does not know and cannot opine on if its client's use of AI products in hiring. Pay Transparency Notice Determining compensation for this role (and others) at Vaco by Highspring depends upon a wide array of factors including but not limited to: the individual's skill sets, experience and training; licensure and certification requirements; office location and other geographic considerations; other business and organizational needs. With that said, as required by local law, Vaco by Highspring believes that the following salary range referenced above reasonably estimates the base compensation for an individual hired into this position in geographies that require salary range disclosure. The individual may also be eligible for discretionary bonuses.
CapGemini
Associate Data Scientist
CapGemini Houston, Texas
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Locations: Houston ,TX - Onsite About the job you're considering: Capgemini is seeking an enthusiastic and driven Junior AI-Native Consultant to join our dynamic Energy & Utilities sector team. This role is designed for emerging talent passionate about leveraging Artificial Intelligence to solve complex industry challenges. You will contribute to innovative projects, applying advanced AI/ML techniques to optimize operations, enhance decision-making, and drive digital transformation for our clients. We are looking for individuals who possess a strong foundational understanding of AI concepts and have a minimum of 15 months of professional experience within the Oracle Field Service Cloud (OFSC), Oil & Gas, or broader Utilities domain. This is a client-facing role that requires excellent communication and problem-solving skills. Your Role: Collaborate with senior consultants and client teams to identify business challenges and opportunities for AI-driven solutions in the Energy & Utilities sector. Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions. Support data collection, cleaning, and preprocessing activities for AI initiatives. Work with leading cloud technologies (Azure, AWS, GCP) and their AI/ML services. Utilize platforms such as Databricks, PySpark, and modern AI frameworks. Develop agentic AI workflows and intelligent agents to automate tasks and improve operational efficiency. Participate in client workshops and presentations, effectively articulating technical concepts to diverse stakeholders. Contribute to project documentation, reports, and client deliverables. Develop reusable assets, demos, and solution accelerators. Stay current with emerging AI technologies and industry trends, particularly within the Energy & Utilities landscape. Foster a collaborative environment, actively sharing knowledge and best practices within the team. Required Qualifications Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field. Minimum of 15 months of professional (non-internship) work experience in data science, AI, or machine learning roles. Demonstrable background in the Energy & Utilities sector, specifically with OFSC (Oracle Field Service Cloud), Oil & Gas, or general Utilities industry knowledge. Foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts. Proficiency in at least one AI-centric programming language (e.g., Python). Experience with: Generative AI concepts (GPT, Claude, LLMs) MLOps, model deployment, and monitoring LangChain and Retrieval-Augmented Generation (RAG) concepts REST APIs, JSON, Authentication, and Integration patterns Deployment tools (Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy) Data engineering principles, including SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis) Strong analytical, problem-solving, and critical thinking skills. Excellent communication, presentation, and interpersonal skills, with proven ability to engage effectively in client-facing situations. Ability to quickly adapt to new technologies and thrive in a fast-paced, evolving environment. Preferred Qualifications: Familiarity with industry-specific tools such as Seeq and historians (e.g., PHD). Experience with any of the following: data visualization tools and techniques Machine Learning frameworks (TensorFlow, PyTorch, scikit-learn) NLP computer vision graph database technology (Neo4J, Ontotext) JIRA / Confluence Prior project or internship experience in a consulting environment. The base compensation range for this role in the posted location is:$46,000 to $111,000. Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) Life and disability insurance Employee assistance programs Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Click the following link for more information on your rights as an Applicant in the United States. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
09/26/2026
Full time
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Locations: Houston ,TX - Onsite About the job you're considering: Capgemini is seeking an enthusiastic and driven Junior AI-Native Consultant to join our dynamic Energy & Utilities sector team. This role is designed for emerging talent passionate about leveraging Artificial Intelligence to solve complex industry challenges. You will contribute to innovative projects, applying advanced AI/ML techniques to optimize operations, enhance decision-making, and drive digital transformation for our clients. We are looking for individuals who possess a strong foundational understanding of AI concepts and have a minimum of 15 months of professional experience within the Oracle Field Service Cloud (OFSC), Oil & Gas, or broader Utilities domain. This is a client-facing role that requires excellent communication and problem-solving skills. Your Role: Collaborate with senior consultants and client teams to identify business challenges and opportunities for AI-driven solutions in the Energy & Utilities sector. Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions. Support data collection, cleaning, and preprocessing activities for AI initiatives. Work with leading cloud technologies (Azure, AWS, GCP) and their AI/ML services. Utilize platforms such as Databricks, PySpark, and modern AI frameworks. Develop agentic AI workflows and intelligent agents to automate tasks and improve operational efficiency. Participate in client workshops and presentations, effectively articulating technical concepts to diverse stakeholders. Contribute to project documentation, reports, and client deliverables. Develop reusable assets, demos, and solution accelerators. Stay current with emerging AI technologies and industry trends, particularly within the Energy & Utilities landscape. Foster a collaborative environment, actively sharing knowledge and best practices within the team. Required Qualifications Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field. Minimum of 15 months of professional (non-internship) work experience in data science, AI, or machine learning roles. Demonstrable background in the Energy & Utilities sector, specifically with OFSC (Oracle Field Service Cloud), Oil & Gas, or general Utilities industry knowledge. Foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts. Proficiency in at least one AI-centric programming language (e.g., Python). Experience with: Generative AI concepts (GPT, Claude, LLMs) MLOps, model deployment, and monitoring LangChain and Retrieval-Augmented Generation (RAG) concepts REST APIs, JSON, Authentication, and Integration patterns Deployment tools (Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy) Data engineering principles, including SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis) Strong analytical, problem-solving, and critical thinking skills. Excellent communication, presentation, and interpersonal skills, with proven ability to engage effectively in client-facing situations. Ability to quickly adapt to new technologies and thrive in a fast-paced, evolving environment. Preferred Qualifications: Familiarity with industry-specific tools such as Seeq and historians (e.g., PHD). Experience with any of the following: data visualization tools and techniques Machine Learning frameworks (TensorFlow, PyTorch, scikit-learn) NLP computer vision graph database technology (Neo4J, Ontotext) JIRA / Confluence Prior project or internship experience in a consulting environment. The base compensation range for this role in the posted location is:$46,000 to $111,000. Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) Life and disability insurance Employee assistance programs Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Click the following link for more information on your rights as an Applicant in the United States. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
STINGRAI PED Cell Implementation Manager (Remote)- 30351
HII's Mission Technologies division Remote, Oregon
Requisition Number: 30351 Required Travel: 11 - 25% Employment Type: Full Time/Salaried/Exempt Anticipated Salary Range: $148,275.00 - $195,000.00 Security Clearance: TS/SCI Level of Experience: Senior HI This opportunity resides with All-Domain Operations (ADO) , a business group within HII's Mission Technologies division. All-Domain Operations comprises multi-domain operations, platforms and logistics, and intelligence operations. HII designs, develops, integrates and manages the sensors, systems and other assets necessary to support integrated ISR operations and accelerated decision-making. With data fusion and mission management capabilities for the Department of Defense, the combatant commands and the intelligence community, HII advances the mission around the globe. Leadership at HII - Mission Technologies HII's Leadership Capability Framework defines the standard of excellence expected of all leaders across Mission Technologies. Leaders are accountable for modeling these capabilities and building them within their teams: Know & Grow Your People - Develop talent, empower teams, and build an inclusive environment. Build Relationships - Strengthen trust, collaboration, and cross-functional partnerships. Take Ownership - Drive accountability, execution excellence, and results. Customer First - Anticipate mission needs and deliver value to our partners. Shape the Future - Inspire innovation and align work with strategic priorities. Act with Urgency - Make informed decisions and move with purpose. These capabilities define how leaders inspire teams, deliver results, and shape the future of Mission Technologies. Summary HII-Mission Technologies is seeking a highly proactive, take-charge Project Manager to lead the planning and implementation of a CONUS based PED (Processing, Exploitation, and Dissemination) Cell. The ideal candidate will have a strong technical foundation, the ability to coordinate multidisciplinary requirements, and the leadership skills necessary to guide teams through the design and deployment of PED capabilities at scale. What You Will Do Lead and manage end-to-end planning, coordination, and execution of the CONUS based PED Cell implementation, including facility/site identification, feasibility, and selection, buildout and construction of the physical space, network and data transport design and accreditation, data and network architecture across full data path from multi-INT ISR collection to dissemination of finished intelligence products to multiple stakeholders with varied access levels and interests. Drive cross functional collaboration to identify, design, and enable data flows and network architectures that support PED operations that can scale to meet an increase in (and diversity of) collection assets. Oversee physical infrastructure preparation, IT systems setup, equipment readiness, security protocol alignment, and network requirements necessary for operational PED support. Serve as the primary project manager, ensuring timelines, risks, deliverables, and dependencies are tracked and communicated effectively. Partner with government stakeholders, technical teams, and operational leads to align requirements and resolve challenges. Apply knowledge of secure facility standards; familiarity with SCIF buildout requirements and ICD 705 guidelines is a strong plus. Maintain clear documentation and manage communication channels to ensure successful coordination across all project participants. What We Are Looking For 8 years relevant progressive experience with Bachelors in related field; 6 years relevant progressive experience with Masters in related field; or High School Diploma or equivalent and 12 years relevant progressive experience. Clearance: Must possess and maintain an active TS/SCI clearance. Demonstrated experience leading complex technical or operational projects with multiple stakeholders. Foundational understanding of physical infrastructure, IT systems, equipment requirements, security protocols, and network support required for standing up high demand operational cell. Proven ability to take initiative, drive actions, and lead teams through ambiguity and evolving requirements. Excellent communication, organizational, and problem solving skills. Understanding of ISR (Intelligence, Surveillance, Reconnaissance) data, formats, and workflows. Familiarity with data exploitation tools and platforms used in PED environments. Knowledge of how data flows through networks, servers, and tools to support real time or near real time operations. Ability to identify and troubleshoot issues with data ingestion, processing, or dissemination. Knowledge of classified handling procedures and secure data workflows. Ability to follow strict protocol around systems access, data protection, and dissemination authorities. Preferred: Bonus Points For Experience supporting PED, intelligence operations, or analytical mission environments. Experience using mission systems or common PED software suites. Ability to process, analyze, and interpret sensor data (imagery, FMV, SIGINT, GEOINT, etc.). Familiarity with SCIF requirements, ICD 705 standards, or classified facility design. Experience designing or enabling data flows or network architectures for mission focused environments. Active Project Management Professional (PMP) certification. The listed salary range for this role is intended as a good faith estimate based on the role's location, expectations, and responsibilities. When extending an offer, HII's Mission Technologies division takes a variety of factors into consideration which include, but are not limited to, the role's function and a candidate's education or training, work experience, and key skills. Meet HII's Mission Technologies Division Our team of more than 7,000 professionals worldwide delivers all-domain expertise and advanced technologies in service of mission partners across the globe. Mission Technologies is leading the next evolution of national defense - the data evolution - by accelerating a breadth of national security solutions for government and commercial customers. Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class. Find the role that's right for you. Apply today. We look forward to meeting you. To learn more about Mission Technologies, click here for a short video: HII is more than a job - it's an opportunity to build a new future. We offer competitive benefits such as best-in-class medical, dental and vision plan choices; wellness resources; employee assistance programs; Savings Plan Options (401(k ; financial planning tools, life insurance; employee discounts; paid holidays and paid time off; tuition reimbursement; as well as early childhood and post-secondary education scholarships. Bonus/other non-recurrent compensation is occasionally offered for qualified positions, and if applicable to this role will be addressed by the recruiter at the screening phase of application. Why HII We build the world's most powerful, survivable naval ships and defense technology solutions that safeguard our seas, sky, land, space and cyber. Our workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration professionals. Recognized as one of America's top large company employers, we are a values and ethics driven organization that puts people's safety and well-being first. Regardless of your role or where you serve, at HII, you'll find a supportive and welcoming environment, competitive benefits, and valuable educational and training programs for continual career growth at every stage of your career. Together we are working to ensure a future where everyone can be free and thrive. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, physical or mental disability, age, or veteran status or any other basis protected by federal, state, or local law. Do You Need Assistance? If you need a reasonable accommodation for any part of the employment process, please send an e-mail to and let us know the nature of your request and your contact information. Reasonable accommodations are considered on a case-by-case basis. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address. Additionally, you may also call 1- for assistance. Press for HII Mission Technologies.
09/26/2026
Full time
Requisition Number: 30351 Required Travel: 11 - 25% Employment Type: Full Time/Salaried/Exempt Anticipated Salary Range: $148,275.00 - $195,000.00 Security Clearance: TS/SCI Level of Experience: Senior HI This opportunity resides with All-Domain Operations (ADO) , a business group within HII's Mission Technologies division. All-Domain Operations comprises multi-domain operations, platforms and logistics, and intelligence operations. HII designs, develops, integrates and manages the sensors, systems and other assets necessary to support integrated ISR operations and accelerated decision-making. With data fusion and mission management capabilities for the Department of Defense, the combatant commands and the intelligence community, HII advances the mission around the globe. Leadership at HII - Mission Technologies HII's Leadership Capability Framework defines the standard of excellence expected of all leaders across Mission Technologies. Leaders are accountable for modeling these capabilities and building them within their teams: Know & Grow Your People - Develop talent, empower teams, and build an inclusive environment. Build Relationships - Strengthen trust, collaboration, and cross-functional partnerships. Take Ownership - Drive accountability, execution excellence, and results. Customer First - Anticipate mission needs and deliver value to our partners. Shape the Future - Inspire innovation and align work with strategic priorities. Act with Urgency - Make informed decisions and move with purpose. These capabilities define how leaders inspire teams, deliver results, and shape the future of Mission Technologies. Summary HII-Mission Technologies is seeking a highly proactive, take-charge Project Manager to lead the planning and implementation of a CONUS based PED (Processing, Exploitation, and Dissemination) Cell. The ideal candidate will have a strong technical foundation, the ability to coordinate multidisciplinary requirements, and the leadership skills necessary to guide teams through the design and deployment of PED capabilities at scale. What You Will Do Lead and manage end-to-end planning, coordination, and execution of the CONUS based PED Cell implementation, including facility/site identification, feasibility, and selection, buildout and construction of the physical space, network and data transport design and accreditation, data and network architecture across full data path from multi-INT ISR collection to dissemination of finished intelligence products to multiple stakeholders with varied access levels and interests. Drive cross functional collaboration to identify, design, and enable data flows and network architectures that support PED operations that can scale to meet an increase in (and diversity of) collection assets. Oversee physical infrastructure preparation, IT systems setup, equipment readiness, security protocol alignment, and network requirements necessary for operational PED support. Serve as the primary project manager, ensuring timelines, risks, deliverables, and dependencies are tracked and communicated effectively. Partner with government stakeholders, technical teams, and operational leads to align requirements and resolve challenges. Apply knowledge of secure facility standards; familiarity with SCIF buildout requirements and ICD 705 guidelines is a strong plus. Maintain clear documentation and manage communication channels to ensure successful coordination across all project participants. What We Are Looking For 8 years relevant progressive experience with Bachelors in related field; 6 years relevant progressive experience with Masters in related field; or High School Diploma or equivalent and 12 years relevant progressive experience. Clearance: Must possess and maintain an active TS/SCI clearance. Demonstrated experience leading complex technical or operational projects with multiple stakeholders. Foundational understanding of physical infrastructure, IT systems, equipment requirements, security protocols, and network support required for standing up high demand operational cell. Proven ability to take initiative, drive actions, and lead teams through ambiguity and evolving requirements. Excellent communication, organizational, and problem solving skills. Understanding of ISR (Intelligence, Surveillance, Reconnaissance) data, formats, and workflows. Familiarity with data exploitation tools and platforms used in PED environments. Knowledge of how data flows through networks, servers, and tools to support real time or near real time operations. Ability to identify and troubleshoot issues with data ingestion, processing, or dissemination. Knowledge of classified handling procedures and secure data workflows. Ability to follow strict protocol around systems access, data protection, and dissemination authorities. Preferred: Bonus Points For Experience supporting PED, intelligence operations, or analytical mission environments. Experience using mission systems or common PED software suites. Ability to process, analyze, and interpret sensor data (imagery, FMV, SIGINT, GEOINT, etc.). Familiarity with SCIF requirements, ICD 705 standards, or classified facility design. Experience designing or enabling data flows or network architectures for mission focused environments. Active Project Management Professional (PMP) certification. The listed salary range for this role is intended as a good faith estimate based on the role's location, expectations, and responsibilities. When extending an offer, HII's Mission Technologies division takes a variety of factors into consideration which include, but are not limited to, the role's function and a candidate's education or training, work experience, and key skills. Meet HII's Mission Technologies Division Our team of more than 7,000 professionals worldwide delivers all-domain expertise and advanced technologies in service of mission partners across the globe. Mission Technologies is leading the next evolution of national defense - the data evolution - by accelerating a breadth of national security solutions for government and commercial customers. Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class. Find the role that's right for you. Apply today. We look forward to meeting you. To learn more about Mission Technologies, click here for a short video: HII is more than a job - it's an opportunity to build a new future. We offer competitive benefits such as best-in-class medical, dental and vision plan choices; wellness resources; employee assistance programs; Savings Plan Options (401(k ; financial planning tools, life insurance; employee discounts; paid holidays and paid time off; tuition reimbursement; as well as early childhood and post-secondary education scholarships. Bonus/other non-recurrent compensation is occasionally offered for qualified positions, and if applicable to this role will be addressed by the recruiter at the screening phase of application. Why HII We build the world's most powerful, survivable naval ships and defense technology solutions that safeguard our seas, sky, land, space and cyber. Our workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration professionals. Recognized as one of America's top large company employers, we are a values and ethics driven organization that puts people's safety and well-being first. Regardless of your role or where you serve, at HII, you'll find a supportive and welcoming environment, competitive benefits, and valuable educational and training programs for continual career growth at every stage of your career. Together we are working to ensure a future where everyone can be free and thrive. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, physical or mental disability, age, or veteran status or any other basis protected by federal, state, or local law. Do You Need Assistance? If you need a reasonable accommodation for any part of the employment process, please send an e-mail to and let us know the nature of your request and your contact information. Reasonable accommodations are considered on a case-by-case basis. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address. Additionally, you may also call 1- for assistance. Press for HII Mission Technologies.
Senior ML Engineer - Cyber Security
Altice USA
Are you looking to Optimize your life? Start your exciting path to a rewarding career today! We are Optimum, a leader in the fast-paced world of connectivity, and we're seeking driven and enthusiastic professionals to join our team, empower lives, fuel businesses, and drive innovation. Connectivity is now longer a luxury, but a necessity. A career at Optimum means you'll be enabling progress and enhancing lives by providing reliable, high-speed connectivity solutions that keep the world connected. Our successes, now and in the future, are powered by our amazing product, a commitment to our people and culture, and the connections we make in our communities. If you are resourceful, collaborative, and passionate about delivering consistent excellence, Optimum is for you! Job Summary As a Senior SOC Engineer (AI & Automation), you will design, build, and operate the AI, automation, and detection-engineering capabilities that power our Security Operations Center. Bridging security operations and software engineering, you will develop AI-driven detection, triage, and response tooling, integrate large language model (LLM) and agentic workflows into analyst operations, and ensure those capabilities are accurate, safe, measurable, and continuously improved. As a senior member of the team, you will also serve as a technical leader during major security incidents, leading investigations and turning lessons learned into stronger detections, automations, and playbooks. Responsibilities • Design, build, and maintain AI/ML- and automation-driven capabilities for alert enrichment, correlation, summarization, triage, and prioritization. • Develop and maintain SOAR automations and detection-as-code pipelines that are version-controlled, tested, and peer-reviewed. • Integrate LLM and agentic AI tooling into SOC workflows (copilots, auto-triage agents); engineer prompts, guardrails, and evaluation harnesses. • Evaluate, benchmark, and tune AI models and tools for security use cases, measuring precision and recall, false-positive reduction, and impact on mean time to detect and respond (MTTD/MTTR). • Build data pipelines and feature engineering from security telemetry to support detection and machine-learning use cases. • Apply MLOps practices, including model versioning, monitoring, drift detection, and retraining, to security models running in production. • Ensure responsible and secure AI use, including data governance, prompt-injection and model-abuse defenses, privacy, and output validation. • Partner with detection engineers, SOC analysts, and incident responders to operationalize tooling and feed lessons learned back into models and automations. • Serve as a senior escalation point and incident commander for complex and major incidents, coordinating cross-functional response and directing technical workstreams. • Lead investigations and forensic analysis for escalated incidents and provide hands-on incident response support across on-premises and cloud environments. • Own post-incident reviews and root cause analyses, translating lessons learned into new detections, automations, and playbook improvements. • Develop, run, and mature incident-response playbooks and tabletop exercises (TTX) to validate and improve organizational readiness. • Define and report detection and incident-response metrics (e.g., MTTD, MTTR) to measure and continuously improve SOC effectiveness. • Mentor analysts and engineers, fostering a culture of continuous learning across AI-augmented and incident-response workflows, and promote an AI-first operating model across the SOC. Qualifications • Bachelor's degree in Computer Science, Engineering, or related field, or equivalent years of experience • 7+ years of combined experience across security operations, incident response, and software engineering • Hands-on incident response and digital forensics experience, including leading or coordinating response to complex and major incidents preffered • Strong programming skills (e.g., Python) and sound software-engineering practices, including version control, CI/CD, and automated testing • Hands-on experience building with AI/ML, including large language models, prompt engineering, retrieval-augmented generation (RAG), and/or agentic frameworks • Experience with SOAR/automation and detection engineering (detection-as-code) • Data engineering skills, including working with large security datasets, APIs, and pipelines • Working knowledge of SOC operations and the incident lifecycle, including the MITRE ATT&CK framework, the NIST incident response lifecycle (NIST SP 800-61), the Cyber Kill Chain, and SANS PICERL • Cloud security and cloud-platform experience • Awareness of AI and LLM security risks, such as prompt injection and the OWASP LLM Top 10 • Ability to translate fluently between security and engineering stakeholders. Preferred Qualifications • MLOps experience deploying and maintaining models in production • Relevant security and/or AI/ML certifications, including incident-response and forensics credentials (e.g., GCIH, GCFA, GCFE, GNFA) or CISSP/CISM At Optimum, every action and interaction we take part in, is driven by our three Guiding Principles: Do What's Right, Drive One Optimum, and Make It Happen. These aren't just words, they help us build trust, create real community, and embrace new ways of thinking. Our employees are empowered to do the right thing for our customers and co-workers and to recognize and reward these behaviors when we see them. It's all part of the bigger picture of "Be The Difference" where each employee knows they have the power to enact real change, share new ideas, and understand that learning never stops. If you have the drive to succeed and are ready to embark on a thrilling career, seize this opportunity today, and join our winning team. Together, we'll shape the future of connectivity. All job descriptions and required skills, qualifications and responsibilities for a particular position are subject to modification by the Company from time to time, in the Company's discretion based on business necessity. We are an Equal Opportunity Employer committed to recruiting, hiring and promoting qualified people of all backgrounds regardless of gender, race, color, creed, national origin, religion, age, marital status, pregnancy, physical or mental disability, sexual orientation, gender identity, military or veteran status, or any other basis protected by federal, state, or local law. The Company collects personal information about its applicants for employment that may include personal identifiers, professional or employment related information, photos, education information and/or protected classifications under federal and state law. This information is collected for employment purposes, including identification, work authorization, FCRA-compliant background screening, human resource administration and compliance with federal, state and local law. Applicants for employment with The Company will never be asked to provide money (even if reimbursable) as part of the job application or hiring process. Please review our Fraud FAQ for further details. Pay is competitive and based on a number of job-related factors, including skills and experience. The starting pay rate/range at time of hire for this position in the posted location is $100,246.00 - $164,689.00 / year. The rate/range provided herein is the anticipated pay at the time of hire, and does not reflect future job opportunity. We appreciate your interest in this opportunity. Applicants must be authorized to work for ANY employer in the U.S. Please note that at this time, we do not provide visa sponsorship for employment.
09/26/2026
Full time
Are you looking to Optimize your life? Start your exciting path to a rewarding career today! We are Optimum, a leader in the fast-paced world of connectivity, and we're seeking driven and enthusiastic professionals to join our team, empower lives, fuel businesses, and drive innovation. Connectivity is now longer a luxury, but a necessity. A career at Optimum means you'll be enabling progress and enhancing lives by providing reliable, high-speed connectivity solutions that keep the world connected. Our successes, now and in the future, are powered by our amazing product, a commitment to our people and culture, and the connections we make in our communities. If you are resourceful, collaborative, and passionate about delivering consistent excellence, Optimum is for you! Job Summary As a Senior SOC Engineer (AI & Automation), you will design, build, and operate the AI, automation, and detection-engineering capabilities that power our Security Operations Center. Bridging security operations and software engineering, you will develop AI-driven detection, triage, and response tooling, integrate large language model (LLM) and agentic workflows into analyst operations, and ensure those capabilities are accurate, safe, measurable, and continuously improved. As a senior member of the team, you will also serve as a technical leader during major security incidents, leading investigations and turning lessons learned into stronger detections, automations, and playbooks. Responsibilities • Design, build, and maintain AI/ML- and automation-driven capabilities for alert enrichment, correlation, summarization, triage, and prioritization. • Develop and maintain SOAR automations and detection-as-code pipelines that are version-controlled, tested, and peer-reviewed. • Integrate LLM and agentic AI tooling into SOC workflows (copilots, auto-triage agents); engineer prompts, guardrails, and evaluation harnesses. • Evaluate, benchmark, and tune AI models and tools for security use cases, measuring precision and recall, false-positive reduction, and impact on mean time to detect and respond (MTTD/MTTR). • Build data pipelines and feature engineering from security telemetry to support detection and machine-learning use cases. • Apply MLOps practices, including model versioning, monitoring, drift detection, and retraining, to security models running in production. • Ensure responsible and secure AI use, including data governance, prompt-injection and model-abuse defenses, privacy, and output validation. • Partner with detection engineers, SOC analysts, and incident responders to operationalize tooling and feed lessons learned back into models and automations. • Serve as a senior escalation point and incident commander for complex and major incidents, coordinating cross-functional response and directing technical workstreams. • Lead investigations and forensic analysis for escalated incidents and provide hands-on incident response support across on-premises and cloud environments. • Own post-incident reviews and root cause analyses, translating lessons learned into new detections, automations, and playbook improvements. • Develop, run, and mature incident-response playbooks and tabletop exercises (TTX) to validate and improve organizational readiness. • Define and report detection and incident-response metrics (e.g., MTTD, MTTR) to measure and continuously improve SOC effectiveness. • Mentor analysts and engineers, fostering a culture of continuous learning across AI-augmented and incident-response workflows, and promote an AI-first operating model across the SOC. Qualifications • Bachelor's degree in Computer Science, Engineering, or related field, or equivalent years of experience • 7+ years of combined experience across security operations, incident response, and software engineering • Hands-on incident response and digital forensics experience, including leading or coordinating response to complex and major incidents preffered • Strong programming skills (e.g., Python) and sound software-engineering practices, including version control, CI/CD, and automated testing • Hands-on experience building with AI/ML, including large language models, prompt engineering, retrieval-augmented generation (RAG), and/or agentic frameworks • Experience with SOAR/automation and detection engineering (detection-as-code) • Data engineering skills, including working with large security datasets, APIs, and pipelines • Working knowledge of SOC operations and the incident lifecycle, including the MITRE ATT&CK framework, the NIST incident response lifecycle (NIST SP 800-61), the Cyber Kill Chain, and SANS PICERL • Cloud security and cloud-platform experience • Awareness of AI and LLM security risks, such as prompt injection and the OWASP LLM Top 10 • Ability to translate fluently between security and engineering stakeholders. Preferred Qualifications • MLOps experience deploying and maintaining models in production • Relevant security and/or AI/ML certifications, including incident-response and forensics credentials (e.g., GCIH, GCFA, GCFE, GNFA) or CISSP/CISM At Optimum, every action and interaction we take part in, is driven by our three Guiding Principles: Do What's Right, Drive One Optimum, and Make It Happen. These aren't just words, they help us build trust, create real community, and embrace new ways of thinking. Our employees are empowered to do the right thing for our customers and co-workers and to recognize and reward these behaviors when we see them. It's all part of the bigger picture of "Be The Difference" where each employee knows they have the power to enact real change, share new ideas, and understand that learning never stops. If you have the drive to succeed and are ready to embark on a thrilling career, seize this opportunity today, and join our winning team. Together, we'll shape the future of connectivity. All job descriptions and required skills, qualifications and responsibilities for a particular position are subject to modification by the Company from time to time, in the Company's discretion based on business necessity. We are an Equal Opportunity Employer committed to recruiting, hiring and promoting qualified people of all backgrounds regardless of gender, race, color, creed, national origin, religion, age, marital status, pregnancy, physical or mental disability, sexual orientation, gender identity, military or veteran status, or any other basis protected by federal, state, or local law. The Company collects personal information about its applicants for employment that may include personal identifiers, professional or employment related information, photos, education information and/or protected classifications under federal and state law. This information is collected for employment purposes, including identification, work authorization, FCRA-compliant background screening, human resource administration and compliance with federal, state and local law. Applicants for employment with The Company will never be asked to provide money (even if reimbursable) as part of the job application or hiring process. Please review our Fraud FAQ for further details. Pay is competitive and based on a number of job-related factors, including skills and experience. The starting pay rate/range at time of hire for this position in the posted location is $100,246.00 - $164,689.00 / year. The rate/range provided herein is the anticipated pay at the time of hire, and does not reflect future job opportunity. We appreciate your interest in this opportunity. Applicants must be authorized to work for ANY employer in the U.S. Please note that at this time, we do not provide visa sponsorship for employment.
Senior ML Engineer - Cyber Security
Altice USA Norwalk, Connecticut
Are you looking to Optimize your life? Start your exciting path to a rewarding career today! We are Optimum, a leader in the fast-paced world of connectivity, and we're seeking driven and enthusiastic professionals to join our team, empower lives, fuel businesses, and drive innovation. Connectivity is now longer a luxury, but a necessity. A career at Optimum means you'll be enabling progress and enhancing lives by providing reliable, high-speed connectivity solutions that keep the world connected. Our successes, now and in the future, are powered by our amazing product, a commitment to our people and culture, and the connections we make in our communities. If you are resourceful, collaborative, and passionate about delivering consistent excellence, Optimum is for you! Job Summary As a Senior SOC Engineer (AI & Automation), you will design, build, and operate the AI, automation, and detection-engineering capabilities that power our Security Operations Center. Bridging security operations and software engineering, you will develop AI-driven detection, triage, and response tooling, integrate large language model (LLM) and agentic workflows into analyst operations, and ensure those capabilities are accurate, safe, measurable, and continuously improved. As a senior member of the team, you will also serve as a technical leader during major security incidents, leading investigations and turning lessons learned into stronger detections, automations, and playbooks. Responsibilities • Design, build, and maintain AI/ML- and automation-driven capabilities for alert enrichment, correlation, summarization, triage, and prioritization. • Develop and maintain SOAR automations and detection-as-code pipelines that are version-controlled, tested, and peer-reviewed. • Integrate LLM and agentic AI tooling into SOC workflows (copilots, auto-triage agents); engineer prompts, guardrails, and evaluation harnesses. • Evaluate, benchmark, and tune AI models and tools for security use cases, measuring precision and recall, false-positive reduction, and impact on mean time to detect and respond (MTTD/MTTR). • Build data pipelines and feature engineering from security telemetry to support detection and machine-learning use cases. • Apply MLOps practices, including model versioning, monitoring, drift detection, and retraining, to security models running in production. • Ensure responsible and secure AI use, including data governance, prompt-injection and model-abuse defenses, privacy, and output validation. • Partner with detection engineers, SOC analysts, and incident responders to operationalize tooling and feed lessons learned back into models and automations. • Serve as a senior escalation point and incident commander for complex and major incidents, coordinating cross-functional response and directing technical workstreams. • Lead investigations and forensic analysis for escalated incidents and provide hands-on incident response support across on-premises and cloud environments. • Own post-incident reviews and root cause analyses, translating lessons learned into new detections, automations, and playbook improvements. • Develop, run, and mature incident-response playbooks and tabletop exercises (TTX) to validate and improve organizational readiness. • Define and report detection and incident-response metrics (e.g., MTTD, MTTR) to measure and continuously improve SOC effectiveness. • Mentor analysts and engineers, fostering a culture of continuous learning across AI-augmented and incident-response workflows, and promote an AI-first operating model across the SOC. Qualifications • Bachelor's degree in Computer Science, Engineering, or related field, or equivalent years of experience • 7+ years of combined experience across security operations, incident response, and software engineering • Hands-on incident response and digital forensics experience, including leading or coordinating response to complex and major incidents preffered • Strong programming skills (e.g., Python) and sound software-engineering practices, including version control, CI/CD, and automated testing • Hands-on experience building with AI/ML, including large language models, prompt engineering, retrieval-augmented generation (RAG), and/or agentic frameworks • Experience with SOAR/automation and detection engineering (detection-as-code) • Data engineering skills, including working with large security datasets, APIs, and pipelines • Working knowledge of SOC operations and the incident lifecycle, including the MITRE ATT&CK framework, the NIST incident response lifecycle (NIST SP 800-61), the Cyber Kill Chain, and SANS PICERL • Cloud security and cloud-platform experience • Awareness of AI and LLM security risks, such as prompt injection and the OWASP LLM Top 10 • Ability to translate fluently between security and engineering stakeholders. Preferred Qualifications • MLOps experience deploying and maintaining models in production • Relevant security and/or AI/ML certifications, including incident-response and forensics credentials (e.g., GCIH, GCFA, GCFE, GNFA) or CISSP/CISM At Optimum, every action and interaction we take part in, is driven by our three Guiding Principles: Do What's Right, Drive One Optimum, and Make It Happen. These aren't just words, they help us build trust, create real community, and embrace new ways of thinking. Our employees are empowered to do the right thing for our customers and co-workers and to recognize and reward these behaviors when we see them. It's all part of the bigger picture of "Be The Difference" where each employee knows they have the power to enact real change, share new ideas, and understand that learning never stops. If you have the drive to succeed and are ready to embark on a thrilling career, seize this opportunity today, and join our winning team. Together, we'll shape the future of connectivity. All job descriptions and required skills, qualifications and responsibilities for a particular position are subject to modification by the Company from time to time, in the Company's discretion based on business necessity. We are an Equal Opportunity Employer committed to recruiting, hiring and promoting qualified people of all backgrounds regardless of gender, race, color, creed, national origin, religion, age, marital status, pregnancy, physical or mental disability, sexual orientation, gender identity, military or veteran status, or any other basis protected by federal, state, or local law. The Company collects personal information about its applicants for employment that may include personal identifiers, professional or employment related information, photos, education information and/or protected classifications under federal and state law. This information is collected for employment purposes, including identification, work authorization, FCRA-compliant background screening, human resource administration and compliance with federal, state and local law. Applicants for employment with The Company will never be asked to provide money (even if reimbursable) as part of the job application or hiring process. Please review our Fraud FAQ for further details. Pay is competitive and based on a number of job-related factors, including skills and experience. The starting pay rate/range at time of hire for this position in the posted location is $100,246.00 - $164,689.00 / year. The rate/range provided herein is the anticipated pay at the time of hire, and does not reflect future job opportunity. We appreciate your interest in this opportunity. Applicants must be authorized to work for ANY employer in the U.S. Please note that at this time, we do not provide visa sponsorship for employment.
09/26/2026
Full time
Are you looking to Optimize your life? Start your exciting path to a rewarding career today! We are Optimum, a leader in the fast-paced world of connectivity, and we're seeking driven and enthusiastic professionals to join our team, empower lives, fuel businesses, and drive innovation. Connectivity is now longer a luxury, but a necessity. A career at Optimum means you'll be enabling progress and enhancing lives by providing reliable, high-speed connectivity solutions that keep the world connected. Our successes, now and in the future, are powered by our amazing product, a commitment to our people and culture, and the connections we make in our communities. If you are resourceful, collaborative, and passionate about delivering consistent excellence, Optimum is for you! Job Summary As a Senior SOC Engineer (AI & Automation), you will design, build, and operate the AI, automation, and detection-engineering capabilities that power our Security Operations Center. Bridging security operations and software engineering, you will develop AI-driven detection, triage, and response tooling, integrate large language model (LLM) and agentic workflows into analyst operations, and ensure those capabilities are accurate, safe, measurable, and continuously improved. As a senior member of the team, you will also serve as a technical leader during major security incidents, leading investigations and turning lessons learned into stronger detections, automations, and playbooks. Responsibilities • Design, build, and maintain AI/ML- and automation-driven capabilities for alert enrichment, correlation, summarization, triage, and prioritization. • Develop and maintain SOAR automations and detection-as-code pipelines that are version-controlled, tested, and peer-reviewed. • Integrate LLM and agentic AI tooling into SOC workflows (copilots, auto-triage agents); engineer prompts, guardrails, and evaluation harnesses. • Evaluate, benchmark, and tune AI models and tools for security use cases, measuring precision and recall, false-positive reduction, and impact on mean time to detect and respond (MTTD/MTTR). • Build data pipelines and feature engineering from security telemetry to support detection and machine-learning use cases. • Apply MLOps practices, including model versioning, monitoring, drift detection, and retraining, to security models running in production. • Ensure responsible and secure AI use, including data governance, prompt-injection and model-abuse defenses, privacy, and output validation. • Partner with detection engineers, SOC analysts, and incident responders to operationalize tooling and feed lessons learned back into models and automations. • Serve as a senior escalation point and incident commander for complex and major incidents, coordinating cross-functional response and directing technical workstreams. • Lead investigations and forensic analysis for escalated incidents and provide hands-on incident response support across on-premises and cloud environments. • Own post-incident reviews and root cause analyses, translating lessons learned into new detections, automations, and playbook improvements. • Develop, run, and mature incident-response playbooks and tabletop exercises (TTX) to validate and improve organizational readiness. • Define and report detection and incident-response metrics (e.g., MTTD, MTTR) to measure and continuously improve SOC effectiveness. • Mentor analysts and engineers, fostering a culture of continuous learning across AI-augmented and incident-response workflows, and promote an AI-first operating model across the SOC. Qualifications • Bachelor's degree in Computer Science, Engineering, or related field, or equivalent years of experience • 7+ years of combined experience across security operations, incident response, and software engineering • Hands-on incident response and digital forensics experience, including leading or coordinating response to complex and major incidents preffered • Strong programming skills (e.g., Python) and sound software-engineering practices, including version control, CI/CD, and automated testing • Hands-on experience building with AI/ML, including large language models, prompt engineering, retrieval-augmented generation (RAG), and/or agentic frameworks • Experience with SOAR/automation and detection engineering (detection-as-code) • Data engineering skills, including working with large security datasets, APIs, and pipelines • Working knowledge of SOC operations and the incident lifecycle, including the MITRE ATT&CK framework, the NIST incident response lifecycle (NIST SP 800-61), the Cyber Kill Chain, and SANS PICERL • Cloud security and cloud-platform experience • Awareness of AI and LLM security risks, such as prompt injection and the OWASP LLM Top 10 • Ability to translate fluently between security and engineering stakeholders. Preferred Qualifications • MLOps experience deploying and maintaining models in production • Relevant security and/or AI/ML certifications, including incident-response and forensics credentials (e.g., GCIH, GCFA, GCFE, GNFA) or CISSP/CISM At Optimum, every action and interaction we take part in, is driven by our three Guiding Principles: Do What's Right, Drive One Optimum, and Make It Happen. These aren't just words, they help us build trust, create real community, and embrace new ways of thinking. Our employees are empowered to do the right thing for our customers and co-workers and to recognize and reward these behaviors when we see them. It's all part of the bigger picture of "Be The Difference" where each employee knows they have the power to enact real change, share new ideas, and understand that learning never stops. If you have the drive to succeed and are ready to embark on a thrilling career, seize this opportunity today, and join our winning team. Together, we'll shape the future of connectivity. All job descriptions and required skills, qualifications and responsibilities for a particular position are subject to modification by the Company from time to time, in the Company's discretion based on business necessity. We are an Equal Opportunity Employer committed to recruiting, hiring and promoting qualified people of all backgrounds regardless of gender, race, color, creed, national origin, religion, age, marital status, pregnancy, physical or mental disability, sexual orientation, gender identity, military or veteran status, or any other basis protected by federal, state, or local law. The Company collects personal information about its applicants for employment that may include personal identifiers, professional or employment related information, photos, education information and/or protected classifications under federal and state law. This information is collected for employment purposes, including identification, work authorization, FCRA-compliant background screening, human resource administration and compliance with federal, state and local law. Applicants for employment with The Company will never be asked to provide money (even if reimbursable) as part of the job application or hiring process. Please review our Fraud FAQ for further details. Pay is competitive and based on a number of job-related factors, including skills and experience. The starting pay rate/range at time of hire for this position in the posted location is $100,246.00 - $164,689.00 / year. The rate/range provided herein is the anticipated pay at the time of hire, and does not reflect future job opportunity. We appreciate your interest in this opportunity. Applicants must be authorized to work for ANY employer in the U.S. Please note that at this time, we do not provide visa sponsorship for employment.
Systems Architect Engineer 4 (VA) - 29420
HII's Mission Technologies division Virginia Beach, Virginia
Requisition Number: 29420 Required Travel: 11 - 25% Employment Type: Full Time/Salaried/Exempt Anticipated Salary Range: $118,372.00 - $169,104.00 Security Clearance: Ability to Obtain Level of Experience: Senior This opportunity resides with Uncrewed Systems (UxS) , a business group within HII's Mission Technologies division. Uncrewed Systems comprises unmanned underwater vehicles (UUVs), unmanned surface vehicles (USVs) and autonomy software. HII creates advanced unmanned solutions for defense, marine research and commercial applications. Serving customers in more than 30 countries, HII provides design, autonomy, manufacturing, testing, operations and sustainment of unmanned systems, including unmanned underwater vehicles (UUVs) and unmanned surface vessels (USVs). Leadership Mindset at HII - Mission Technologies Leadership at HII is a mindset, not a title. Through our Leadership Capability Framework, we define how every employee grows, leads, and contributes-regardless of role. It sets the standard for how you can develop yourself and what you can expect from leaders across our organization. We look for candidates who want to grow in alignment with these capabilities: Know & Grow Your People - Commit to learning and supporting team success. Build Relationships - Communicate openly, collaborate well, and build trust. Take Ownership - Deliver on commitments and take pride in your work. Customer First - Focus on the mission and those we serve. Shape the Future - Bring ideas, curiosity, and continuous improvement. Act with Urgency - Take initiative and follow through with purpose. These capabilities guide how all employees contribute to our shared success across Mission Technologies. Come join HII Where hard stuff is done right! HII Unmanned Systems is seeking a Perception Architect to join our Maritime Autonomy/AI Team. This role involves architecting, developing, integrating, and maintaining sensor perception capabilities deployed across HII's range of maritime platforms. You will work with the team to continuously add capability and demonstrate the solution to customers in real-world scenarios on HII REMUS and ROMULUS platforms. Sensors will span the spectrum of modalities, including EO, IR, acoustics, passive and active RF. Responsibilities Architect and adapt cutting-edge AI/ML algorithms running on the Odyssey perception autonomy stack Architect real-time tracking and sensor fusion systems Create interfacing software to autonomously control sensors Interact with the customers to understand their use cases and requirements Drive execution of simulation tooling to exercise perception pipelines Build and optimize AI/ML pipelines on edge hardware Participate in field testing and rapid hardware iteration What you will be doing Designs and develops system architectures, and defines key capabilities and performance requirements. Defines total systems design and technology maturity constraints in accordance with mission requirements. Develops system element architecture and design and interface definitions. Defines system implementation approach and operational concept. Develops models and architectural guidelines for current and future system development. What we are looking for 9 years relevant experience with Bachelors in related field; 7 years relevant experience with Masters in related field; 4 years relevant experience with PhD or Juris Doctorate in related field; or High School Diploma or equivalent and 13 years relevant experience. MS or PhD in Computer Engineering, Robotic Engineering, Computer Science, or equivalent OR 5+ years of relevant experience Prior experience with software development Prior experience with autonomous platforms Understanding of multiple sensor modalities and underlying physics (e.g., EO, IR, lidar, radar, sonar, acoustics, etc.) Understanding of detection, classification, and identification phenomonology Experience training and deploying ML algorithms (python, pytorch, tensorflow) Experience with estimation, tracking, and fusion algorithms Bonus Points for Strong tracking and sensor fusion background Experience with maritime platforms Current U.S. SECRET security clearance Physical Requirements May require working in an office, industrial, shipboard, or laboratory environment. Capable of climbing ladders and tolerating confined spaces and extreme temperature variances. The listed salary range for this role is intended as a good faith estimate based on the role's location, expectations, and responsibilities. When extending an offer, HII's Mission Technologies division takes a variety of factors into consideration which include, but are not limited to, the role's function and a candidate's education or training, work experience, and key skills. Meet HII's Mission Technologies Division Our team of more than 7,000 professionals worldwide delivers all-domain expertise and advanced technologies in service of mission partners across the globe. Mission Technologies is leading the next evolution of national defense - the data evolution - by accelerating a breadth of national security solutions for government and commercial customers. Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class. Find the role that's right for you. Apply today. We look forward to meeting you. To learn more about Mission Technologies, click here for a short video: HII is more than a job - it's an opportunity to build a new future. We offer competitive benefits such as best-in-class medical, dental and vision plan choices; wellness resources; employee assistance programs; Savings Plan Options (401(k ; financial planning tools, life insurance; employee discounts; paid holidays and paid time off; tuition reimbursement; as well as early childhood and post-secondary education scholarships. Bonus/other non-recurrent compensation is occasionally offered for qualified positions, and if applicable to this role will be addressed by the recruiter at the screening phase of application. Why HII We build the world's most powerful, survivable naval ships and defense technology solutions that safeguard our seas, sky, land, space and cyber. Our workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration professionals. Recognized as one of America's top large company employers, we are a values and ethics driven organization that puts people's safety and well-being first. Regardless of your role or where you serve, at HII, you'll find a supportive and welcoming environment, competitive benefits, and valuable educational and training programs for continual career growth at every stage of your career. Together we are working to ensure a future where everyone can be free and thrive. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, physical or mental disability, age, or veteran status or any other basis protected by federal, state, or local law. Do You Need Assistance? If you need a reasonable accommodation for any part of the employment process, please send an e-mail to and let us know the nature of your request and your contact information. Reasonable accommodations are considered on a case-by-case basis. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address. Additionally, you may also call 1- for assistance. Press for HII Mission Technologies.
09/26/2026
Full time
Requisition Number: 29420 Required Travel: 11 - 25% Employment Type: Full Time/Salaried/Exempt Anticipated Salary Range: $118,372.00 - $169,104.00 Security Clearance: Ability to Obtain Level of Experience: Senior This opportunity resides with Uncrewed Systems (UxS) , a business group within HII's Mission Technologies division. Uncrewed Systems comprises unmanned underwater vehicles (UUVs), unmanned surface vehicles (USVs) and autonomy software. HII creates advanced unmanned solutions for defense, marine research and commercial applications. Serving customers in more than 30 countries, HII provides design, autonomy, manufacturing, testing, operations and sustainment of unmanned systems, including unmanned underwater vehicles (UUVs) and unmanned surface vessels (USVs). Leadership Mindset at HII - Mission Technologies Leadership at HII is a mindset, not a title. Through our Leadership Capability Framework, we define how every employee grows, leads, and contributes-regardless of role. It sets the standard for how you can develop yourself and what you can expect from leaders across our organization. We look for candidates who want to grow in alignment with these capabilities: Know & Grow Your People - Commit to learning and supporting team success. Build Relationships - Communicate openly, collaborate well, and build trust. Take Ownership - Deliver on commitments and take pride in your work. Customer First - Focus on the mission and those we serve. Shape the Future - Bring ideas, curiosity, and continuous improvement. Act with Urgency - Take initiative and follow through with purpose. These capabilities guide how all employees contribute to our shared success across Mission Technologies. Come join HII Where hard stuff is done right! HII Unmanned Systems is seeking a Perception Architect to join our Maritime Autonomy/AI Team. This role involves architecting, developing, integrating, and maintaining sensor perception capabilities deployed across HII's range of maritime platforms. You will work with the team to continuously add capability and demonstrate the solution to customers in real-world scenarios on HII REMUS and ROMULUS platforms. Sensors will span the spectrum of modalities, including EO, IR, acoustics, passive and active RF. Responsibilities Architect and adapt cutting-edge AI/ML algorithms running on the Odyssey perception autonomy stack Architect real-time tracking and sensor fusion systems Create interfacing software to autonomously control sensors Interact with the customers to understand their use cases and requirements Drive execution of simulation tooling to exercise perception pipelines Build and optimize AI/ML pipelines on edge hardware Participate in field testing and rapid hardware iteration What you will be doing Designs and develops system architectures, and defines key capabilities and performance requirements. Defines total systems design and technology maturity constraints in accordance with mission requirements. Develops system element architecture and design and interface definitions. Defines system implementation approach and operational concept. Develops models and architectural guidelines for current and future system development. What we are looking for 9 years relevant experience with Bachelors in related field; 7 years relevant experience with Masters in related field; 4 years relevant experience with PhD or Juris Doctorate in related field; or High School Diploma or equivalent and 13 years relevant experience. MS or PhD in Computer Engineering, Robotic Engineering, Computer Science, or equivalent OR 5+ years of relevant experience Prior experience with software development Prior experience with autonomous platforms Understanding of multiple sensor modalities and underlying physics (e.g., EO, IR, lidar, radar, sonar, acoustics, etc.) Understanding of detection, classification, and identification phenomonology Experience training and deploying ML algorithms (python, pytorch, tensorflow) Experience with estimation, tracking, and fusion algorithms Bonus Points for Strong tracking and sensor fusion background Experience with maritime platforms Current U.S. SECRET security clearance Physical Requirements May require working in an office, industrial, shipboard, or laboratory environment. Capable of climbing ladders and tolerating confined spaces and extreme temperature variances. The listed salary range for this role is intended as a good faith estimate based on the role's location, expectations, and responsibilities. When extending an offer, HII's Mission Technologies division takes a variety of factors into consideration which include, but are not limited to, the role's function and a candidate's education or training, work experience, and key skills. Meet HII's Mission Technologies Division Our team of more than 7,000 professionals worldwide delivers all-domain expertise and advanced technologies in service of mission partners across the globe. Mission Technologies is leading the next evolution of national defense - the data evolution - by accelerating a breadth of national security solutions for government and commercial customers. Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class. Find the role that's right for you. Apply today. We look forward to meeting you. To learn more about Mission Technologies, click here for a short video: HII is more than a job - it's an opportunity to build a new future. We offer competitive benefits such as best-in-class medical, dental and vision plan choices; wellness resources; employee assistance programs; Savings Plan Options (401(k ; financial planning tools, life insurance; employee discounts; paid holidays and paid time off; tuition reimbursement; as well as early childhood and post-secondary education scholarships. Bonus/other non-recurrent compensation is occasionally offered for qualified positions, and if applicable to this role will be addressed by the recruiter at the screening phase of application. Why HII We build the world's most powerful, survivable naval ships and defense technology solutions that safeguard our seas, sky, land, space and cyber. Our workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration professionals. Recognized as one of America's top large company employers, we are a values and ethics driven organization that puts people's safety and well-being first. Regardless of your role or where you serve, at HII, you'll find a supportive and welcoming environment, competitive benefits, and valuable educational and training programs for continual career growth at every stage of your career. Together we are working to ensure a future where everyone can be free and thrive. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, physical or mental disability, age, or veteran status or any other basis protected by federal, state, or local law. Do You Need Assistance? If you need a reasonable accommodation for any part of the employment process, please send an e-mail to and let us know the nature of your request and your contact information. Reasonable accommodations are considered on a case-by-case basis. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this email address. Additionally, you may also call 1- for assistance. Press for HII Mission Technologies.
Elsevier
Senior ML Ops Engineer
Elsevier
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Senior ML Ops Engineer
Remitly
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Senior ML Ops Engineer
Remitly
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Senior ML Ops Engineer
Remitly
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Senior ML Ops Engineer
Remitly
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Elsevier
Senior ML Ops Engineer
Elsevier
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Elsevier
Senior ML Ops Engineer
Elsevier
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Elsevier
Senior ML Ops Engineer
Elsevier
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Elsevier
Senior ML Ops Engineer
Elsevier
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Senior ML Ops Engineer
Remitly
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
09/26/2026
Full time
Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.
Leidos
Principal Data Engineer
Leidos Bethesda, Maryland
Leidos has an exciting opportunity for a Data Engineer in our Intel Sector's Analysis Solutions Business Area. Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in National Security! Job Summary We are seeking an experienced Data Engineer to execute the design, development and administration of an enterprise-scale Next Generation Correlation/Entity Resolution platform. This position supports a mission-critical system that serves as a foundational data exploitation capability servicing multiple applications/use cases. The ideal candidate will possess deep expertise in master data management, probabilistic matching algorithms and entity resolution, with the technical architecture skills required to optimize match performance at scale. This role supports technical planning, design, development, integration, and verification and validation. This role refines customer roadmaps, enterprise epics, and strategic requirements into detailed requirements and actionable user stories. This role coordinates with the team leadership to prioritize user stories that realize customer requirements. Primary Responsibilities: Platform Development & Administration: Design, develop, and maintain probabilistic matching configurations, algorithms, and scoring models to ensure accurate entity resolution across multi-domain data sources. Entity Relationship Management: Analyze and connect records to determine relationships across datasets, creating accurate master data views that improve data quality and compliance readiness. Full Lifecycle Management: Oversee data model design, implementation, testing, deployment, and environment administration to ensure high availability and performance. Matching & Resolution Expertise: Configure and optimize standardization, bucketing, and comparison algorithms; design custom rules, weights, and thresholds; and apply advanced techniques to consolidate records across disparate sources. Quality & Effectiveness Monitoring: Perform match tuning, false positive/negative analysis, threshold optimization, and maintain data quality scorecards and effectiveness metrics. Performance & Scalability: Optimize database performance through indexing, partitioning, and query tuning; monitor systems; and conduct capacity planning and performance testing. Collaboration & Leadership: Partner with stakeholders to translate requirements into solutions, document architecture and procedures, and participate in incident response and root cause analysis. Basic Qualifications: Hands-on experience with probabilistic matching and entity resolution solutions, including translating business requirements into technical configurations Strong knowledge of entity resolution concepts, data linkage theory, and matching algorithms (Fellegi-Sunter, distance metrics, phonetic approaches) Expertise in data quality dimensions, tokenization, standardization, and normalization techniques to improve matching effectiveness Advanced analytical and problem-solving skills with proven experience in data analysis and pattern recognition Proficiency in SQL and enterprise relational databases (Oracle) within large-scale environments, including performance tuning for high-volume transactional systems Experience with enterprise ETL platforms, data integration tools, and maintaining large-scale, cloud-based Linux information systems Familiarity with Agile development methodologies and collaborative software delivery practices BS degree with 12 or more years of relevant experience; or Masters degree with 10 or more years of relevant experience. Will consider additional relevant work experience in lieu of a degree. Must have an active TS/SCI with polygraph security clearance Preferred Qualifications: Background in statistics, data science, or computational linguistics with hands-on experience with enterprise Master Data Management (MDM) platforms (e.g., IBM InfoSphere MDM) Experience with IBM InfoSphere MDM administrative tools, workbench, and configuration utilities Knowledge of probabilistic matching engines including standardization algorithms, bucketing strategies, comparison functions, and scoring models and familiarity with identity resolution in multi-domain environments and machine learning approaches to entity resolution and record linkage Experience in healthcare, financial services, or other industries with complex entity matching requirements Professional certification in Master Data Management, Data Quality or Database Administration Experience with development in Commercial Cloud Platforms (e.g., AWS, Oracle, Azure) and leveraging cloud data services (e.g., S3, RDS, SQS) Familiarity with Java or similar programming languages for custom extensions and matching algorithm development At Leidos, the opportunities are boundless. We challenge our staff with interesting assignments that allow them to thrive professionally and personally. For us, helping you grow your career is good business. We look forward to learning more about you - apply today. If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares. Original Posting: January 29, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $131,300.00 - $237,350.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
09/26/2026
Full time
Leidos has an exciting opportunity for a Data Engineer in our Intel Sector's Analysis Solutions Business Area. Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in National Security! Job Summary We are seeking an experienced Data Engineer to execute the design, development and administration of an enterprise-scale Next Generation Correlation/Entity Resolution platform. This position supports a mission-critical system that serves as a foundational data exploitation capability servicing multiple applications/use cases. The ideal candidate will possess deep expertise in master data management, probabilistic matching algorithms and entity resolution, with the technical architecture skills required to optimize match performance at scale. This role supports technical planning, design, development, integration, and verification and validation. This role refines customer roadmaps, enterprise epics, and strategic requirements into detailed requirements and actionable user stories. This role coordinates with the team leadership to prioritize user stories that realize customer requirements. Primary Responsibilities: Platform Development & Administration: Design, develop, and maintain probabilistic matching configurations, algorithms, and scoring models to ensure accurate entity resolution across multi-domain data sources. Entity Relationship Management: Analyze and connect records to determine relationships across datasets, creating accurate master data views that improve data quality and compliance readiness. Full Lifecycle Management: Oversee data model design, implementation, testing, deployment, and environment administration to ensure high availability and performance. Matching & Resolution Expertise: Configure and optimize standardization, bucketing, and comparison algorithms; design custom rules, weights, and thresholds; and apply advanced techniques to consolidate records across disparate sources. Quality & Effectiveness Monitoring: Perform match tuning, false positive/negative analysis, threshold optimization, and maintain data quality scorecards and effectiveness metrics. Performance & Scalability: Optimize database performance through indexing, partitioning, and query tuning; monitor systems; and conduct capacity planning and performance testing. Collaboration & Leadership: Partner with stakeholders to translate requirements into solutions, document architecture and procedures, and participate in incident response and root cause analysis. Basic Qualifications: Hands-on experience with probabilistic matching and entity resolution solutions, including translating business requirements into technical configurations Strong knowledge of entity resolution concepts, data linkage theory, and matching algorithms (Fellegi-Sunter, distance metrics, phonetic approaches) Expertise in data quality dimensions, tokenization, standardization, and normalization techniques to improve matching effectiveness Advanced analytical and problem-solving skills with proven experience in data analysis and pattern recognition Proficiency in SQL and enterprise relational databases (Oracle) within large-scale environments, including performance tuning for high-volume transactional systems Experience with enterprise ETL platforms, data integration tools, and maintaining large-scale, cloud-based Linux information systems Familiarity with Agile development methodologies and collaborative software delivery practices BS degree with 12 or more years of relevant experience; or Masters degree with 10 or more years of relevant experience. Will consider additional relevant work experience in lieu of a degree. Must have an active TS/SCI with polygraph security clearance Preferred Qualifications: Background in statistics, data science, or computational linguistics with hands-on experience with enterprise Master Data Management (MDM) platforms (e.g., IBM InfoSphere MDM) Experience with IBM InfoSphere MDM administrative tools, workbench, and configuration utilities Knowledge of probabilistic matching engines including standardization algorithms, bucketing strategies, comparison functions, and scoring models and familiarity with identity resolution in multi-domain environments and machine learning approaches to entity resolution and record linkage Experience in healthcare, financial services, or other industries with complex entity matching requirements Professional certification in Master Data Management, Data Quality or Database Administration Experience with development in Commercial Cloud Platforms (e.g., AWS, Oracle, Azure) and leveraging cloud data services (e.g., S3, RDS, SQS) Familiarity with Java or similar programming languages for custom extensions and matching algorithm development At Leidos, the opportunities are boundless. We challenge our staff with interesting assignments that allow them to thrive professionally and personally. For us, helping you grow your career is good business. We look forward to learning more about you - apply today. If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares. Original Posting: January 29, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $131,300.00 - $237,350.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Matterport - Lead Machine Learning R&D Engineer
CoStar Group Sunnyvale, California
Matterport - Lead Machine Learning R&D Engineer Job Description CoStar Group is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P 500 Index, CoStar Group is on a mission to digitize the world's real estate, empowering all people to discover properties, insights and connections that improve their businesses and lives. We have been living and breathing the world of real estate information and online marketplaces for over 35 years, giving us the perspective to create truly unique and valuable offerings to our customers. We've continually refined, transformed, and perfected our approach to our business, creating a language that has become standard in our industry, for our customers, and even our competitors. We continue that effort today and are always working to improve and drive innovation. This is how we deliver for our customers, our employees, and investors. By equipping the brightest minds with the best resources available, we provide an invaluable edge in real estate. About Matterport: Matterport is leading the digital transformation of the built world. Our groundbreaking spatial computing platform turns buildings into data making every space more valuable and accessible. Millions of buildings in more than 170 countries have been transformed into immersive Matterport digital twins to improve every part of the building lifecycle from planning, construction, and operations to documentation, appraisal, and marketing. About the Role: As a Lead Machine Learning R&D Engineer at Matterport, a part of CoStar Group, you will be at the forefront of innovating and advancing our spatial computing platform. You will play a critical role in researching, designing, and implementing cutting-edge machine learning algorithms and models that enhance our ability to digitize the built world, transform physical spaces into rich digital twins, extract valuable insights from them, and create delightful user experiences that make it easy for our customers to modify and interact with their digital twins. This role requires a deep understanding of ML principles, a passion for solving complex real-world problems in 3D data, computer vision, and a desire to contribute to a product that is revolutionizing how people interact with and understand real estate. You will work within a dynamic R&D environment, collaborating closely with fellow engineers, researchers, and product teams to translate groundbreaking ideas into tangible features that empower our users and expand the capabilities of our platform. This is a remote position. Responsibilities: Conduct cutting-edge research in machine learning, computer vision, and 3D data processing to develop novel algorithms and models for spatial understanding and digital twin creation. Design, implement, and optimize robust and scalable ML systems and pipelines for processing large-scale 3D datasets, including point clouds, meshes, and images. Translate research prototypes into production-ready solutions, collaborating closely with engineering teams to integrate ML models into Matterport's core platform. Evaluate and benchmark model performance, identify areas for improvement, and drive iterative enhancements to our ML capabilities. Stay up-to-date with the latest advancements in ML research and industry trends, and proactively identify opportunities to apply new techniques to Matterport's challenges. Collaborate with cross-functional teams including product managers, software engineers, and other researchers to define project requirements, explore technical feasibility, and deliver high-impact features. Present research findings and technical solutions to internal teams and potentially the broader ML community. Contribute to the architectural design and strategic roadmap of Matterport's ML systems and research initiatives. Contribute to the intellectual property of Matterport through patents and publications. Basic Qualifications: Bachelor's Degree required from an accredited, not for profit university or college. A track record of commitment to prior employers 3+ years of experience in machine learning research and development, with a strong focus on computer vision, 3D data processing, or related areas. Proficiency in Pytorch and strong programming skills in Python. Solid understanding of machine learning fundamentals, including deep learning architectures (e.g., CNNs, Transformers), optimization techniques, and evaluation methodologies. Experience with data manipulation and analysis libraries (e.g., NumPy, Pandas). Demonstrated ability to conduct independent research, propose novel solutions, and implement them effectively. Excellent problem-solving skills and the ability to work with complex, real-world datasets. Strong verbal and written communication skills. Preferred Qualifications & Skills: Ph.D. or Masters Degree in Computer Science, Computer Vision, Machine Learning, Robotics, or a related quantitative field. 5+ years of industry experience in applied machine learning research and development, particularly with shipping models to production. Demonstrated expertise in one or more of the following areas: neural rendering (e.g., Gaussian splatting, NeRFs, large reconstruction models, world models), 3D computer vision (e.g., SLAM, 3D reconstruction, point cloud processing, mesh processing), image/video generation models, 2D/3D semantic understanding, depth estimation. Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices. Strong track record of publications in top-tier conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, SIGGRAPH) or significant contributions to open-source projects. Experience mentoring junior engineers or leading technical projects. Excellent communication skills, both written and verbal, with the ability to articulate complex technical concepts to a diverse audience. Perks & Benefits: When you join CoStar Group, you'll experience a collaborative and innovative culture working alongside the best and brightest to empower our people and customers to succeed. We offer you generous compensation and performance-based incentives. CoStar Group also invests in your professional and academic growth with internal training and tuition reimbursement. Our benefits package includes (but is not limited to): Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug Life, legal, and supplementary insurance Virtual and in person mental health counseling services for individuals and family Commuter and parking benefits 401(K) retirement plan with matching contributions Employee stock purchase plan Paid time off Tuition reimbursement On-site fitness center and/or reimbursed fitness center membership costs (location dependent) Access to CoStar Group's Employee Resource Groups Pay Transparency: This position offers an annual pay range from $270,000 - $307,000 determined by relevant skills and experience, and a generous benefits plan. CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing
09/26/2026
Full time
Matterport - Lead Machine Learning R&D Engineer Job Description CoStar Group is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P 500 Index, CoStar Group is on a mission to digitize the world's real estate, empowering all people to discover properties, insights and connections that improve their businesses and lives. We have been living and breathing the world of real estate information and online marketplaces for over 35 years, giving us the perspective to create truly unique and valuable offerings to our customers. We've continually refined, transformed, and perfected our approach to our business, creating a language that has become standard in our industry, for our customers, and even our competitors. We continue that effort today and are always working to improve and drive innovation. This is how we deliver for our customers, our employees, and investors. By equipping the brightest minds with the best resources available, we provide an invaluable edge in real estate. About Matterport: Matterport is leading the digital transformation of the built world. Our groundbreaking spatial computing platform turns buildings into data making every space more valuable and accessible. Millions of buildings in more than 170 countries have been transformed into immersive Matterport digital twins to improve every part of the building lifecycle from planning, construction, and operations to documentation, appraisal, and marketing. About the Role: As a Lead Machine Learning R&D Engineer at Matterport, a part of CoStar Group, you will be at the forefront of innovating and advancing our spatial computing platform. You will play a critical role in researching, designing, and implementing cutting-edge machine learning algorithms and models that enhance our ability to digitize the built world, transform physical spaces into rich digital twins, extract valuable insights from them, and create delightful user experiences that make it easy for our customers to modify and interact with their digital twins. This role requires a deep understanding of ML principles, a passion for solving complex real-world problems in 3D data, computer vision, and a desire to contribute to a product that is revolutionizing how people interact with and understand real estate. You will work within a dynamic R&D environment, collaborating closely with fellow engineers, researchers, and product teams to translate groundbreaking ideas into tangible features that empower our users and expand the capabilities of our platform. This is a remote position. Responsibilities: Conduct cutting-edge research in machine learning, computer vision, and 3D data processing to develop novel algorithms and models for spatial understanding and digital twin creation. Design, implement, and optimize robust and scalable ML systems and pipelines for processing large-scale 3D datasets, including point clouds, meshes, and images. Translate research prototypes into production-ready solutions, collaborating closely with engineering teams to integrate ML models into Matterport's core platform. Evaluate and benchmark model performance, identify areas for improvement, and drive iterative enhancements to our ML capabilities. Stay up-to-date with the latest advancements in ML research and industry trends, and proactively identify opportunities to apply new techniques to Matterport's challenges. Collaborate with cross-functional teams including product managers, software engineers, and other researchers to define project requirements, explore technical feasibility, and deliver high-impact features. Present research findings and technical solutions to internal teams and potentially the broader ML community. Contribute to the architectural design and strategic roadmap of Matterport's ML systems and research initiatives. Contribute to the intellectual property of Matterport through patents and publications. Basic Qualifications: Bachelor's Degree required from an accredited, not for profit university or college. A track record of commitment to prior employers 3+ years of experience in machine learning research and development, with a strong focus on computer vision, 3D data processing, or related areas. Proficiency in Pytorch and strong programming skills in Python. Solid understanding of machine learning fundamentals, including deep learning architectures (e.g., CNNs, Transformers), optimization techniques, and evaluation methodologies. Experience with data manipulation and analysis libraries (e.g., NumPy, Pandas). Demonstrated ability to conduct independent research, propose novel solutions, and implement them effectively. Excellent problem-solving skills and the ability to work with complex, real-world datasets. Strong verbal and written communication skills. Preferred Qualifications & Skills: Ph.D. or Masters Degree in Computer Science, Computer Vision, Machine Learning, Robotics, or a related quantitative field. 5+ years of industry experience in applied machine learning research and development, particularly with shipping models to production. Demonstrated expertise in one or more of the following areas: neural rendering (e.g., Gaussian splatting, NeRFs, large reconstruction models, world models), 3D computer vision (e.g., SLAM, 3D reconstruction, point cloud processing, mesh processing), image/video generation models, 2D/3D semantic understanding, depth estimation. Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices. Strong track record of publications in top-tier conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, SIGGRAPH) or significant contributions to open-source projects. Experience mentoring junior engineers or leading technical projects. Excellent communication skills, both written and verbal, with the ability to articulate complex technical concepts to a diverse audience. Perks & Benefits: When you join CoStar Group, you'll experience a collaborative and innovative culture working alongside the best and brightest to empower our people and customers to succeed. We offer you generous compensation and performance-based incentives. CoStar Group also invests in your professional and academic growth with internal training and tuition reimbursement. Our benefits package includes (but is not limited to): Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug Life, legal, and supplementary insurance Virtual and in person mental health counseling services for individuals and family Commuter and parking benefits 401(K) retirement plan with matching contributions Employee stock purchase plan Paid time off Tuition reimbursement On-site fitness center and/or reimbursed fitness center membership costs (location dependent) Access to CoStar Group's Employee Resource Groups Pay Transparency: This position offers an annual pay range from $270,000 - $307,000 determined by relevant skills and experience, and a generous benefits plan. CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing
Staff Research Engineer, SWE
Turing Seattle, Washington
About Turing Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world's leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents UI-Environments for Computer-Use/Browser-Use agents MCP-based Environments for general function-calling agents across various enterprise and consumer applications We are seeking Staff Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. What You'll Do 1. Conduct Research on Frontier AI Systems Investigate the capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that can inform Turing's products, platforms, and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution. 2. Build and Evaluate Research Systems Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI and machine learning tools. Analyze results carefully and draw clear, evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight. 3. Translate Research into Practical Impact Collaborate closely with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing's products, platforms, and AI capabilities. Help identify which ideas are ready to move from exploration into scalable, real-world applications. Communicate technical findings clearly to both specialized and cross-functional audiences. 4. Contribute to the Research Community Share findings through technical reports, publications, open-source work, workshops, or conference participation where appropriate. Contribute to Turing's research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community. What We're Looking For Research background: PhD or Master's degree in artificial intelligence, machine learning, computer science, or a closely related technical field; exceptional equivalent research experience will also be considered. Technical depth: Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling. Relevant expertise: Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks. Research engineering ability: Strong programming skills and the ability to implement, test, and iterate quickly in a research environment. Scientific judgment: Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making. Communication and collaboration: Clear written and verbal communication skills, intellectual curiosity, and the ability to work effectively across research and engineering teams. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents' ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. This role is required to be in office five days a week, based in any of Turing's offices in San Francisco, Palo Alto, or Seattle. Compensation: $250,000 to $400,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here.
09/26/2026
Full time
About Turing Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world's leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents UI-Environments for Computer-Use/Browser-Use agents MCP-based Environments for general function-calling agents across various enterprise and consumer applications We are seeking Staff Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. What You'll Do 1. Conduct Research on Frontier AI Systems Investigate the capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that can inform Turing's products, platforms, and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution. 2. Build and Evaluate Research Systems Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI and machine learning tools. Analyze results carefully and draw clear, evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight. 3. Translate Research into Practical Impact Collaborate closely with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing's products, platforms, and AI capabilities. Help identify which ideas are ready to move from exploration into scalable, real-world applications. Communicate technical findings clearly to both specialized and cross-functional audiences. 4. Contribute to the Research Community Share findings through technical reports, publications, open-source work, workshops, or conference participation where appropriate. Contribute to Turing's research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community. What We're Looking For Research background: PhD or Master's degree in artificial intelligence, machine learning, computer science, or a closely related technical field; exceptional equivalent research experience will also be considered. Technical depth: Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling. Relevant expertise: Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks. Research engineering ability: Strong programming skills and the ability to implement, test, and iterate quickly in a research environment. Scientific judgment: Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making. Communication and collaboration: Clear written and verbal communication skills, intellectual curiosity, and the ability to work effectively across research and engineering teams. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents' ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. This role is required to be in office five days a week, based in any of Turing's offices in San Francisco, Palo Alto, or Seattle. Compensation: $250,000 to $400,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here.
Staff Research Engineer, SWE
Turing Palo Alto, California
About Turing Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world's leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents UI-Environments for Computer-Use/Browser-Use agents MCP-based Environments for general function-calling agents across various enterprise and consumer applications We are seeking Staff Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. What You'll Do 1. Conduct Research on Frontier AI Systems Investigate the capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that can inform Turing's products, platforms, and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution. 2. Build and Evaluate Research Systems Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI and machine learning tools. Analyze results carefully and draw clear, evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight. 3. Translate Research into Practical Impact Collaborate closely with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing's products, platforms, and AI capabilities. Help identify which ideas are ready to move from exploration into scalable, real-world applications. Communicate technical findings clearly to both specialized and cross-functional audiences. 4. Contribute to the Research Community Share findings through technical reports, publications, open-source work, workshops, or conference participation where appropriate. Contribute to Turing's research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community. What We're Looking For Research background: PhD or Master's degree in artificial intelligence, machine learning, computer science, or a closely related technical field; exceptional equivalent research experience will also be considered. Technical depth: Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling. Relevant expertise: Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks. Research engineering ability: Strong programming skills and the ability to implement, test, and iterate quickly in a research environment. Scientific judgment: Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making. Communication and collaboration: Clear written and verbal communication skills, intellectual curiosity, and the ability to work effectively across research and engineering teams. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents' ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. This role is required to be in office five days a week, based in any of Turing's offices in San Francisco, Palo Alto, or Seattle. Compensation: $250,000 to $400,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here.
09/26/2026
Full time
About Turing Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world's leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents UI-Environments for Computer-Use/Browser-Use agents MCP-based Environments for general function-calling agents across various enterprise and consumer applications We are seeking Staff Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. What You'll Do 1. Conduct Research on Frontier AI Systems Investigate the capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that can inform Turing's products, platforms, and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution. 2. Build and Evaluate Research Systems Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI and machine learning tools. Analyze results carefully and draw clear, evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight. 3. Translate Research into Practical Impact Collaborate closely with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing's products, platforms, and AI capabilities. Help identify which ideas are ready to move from exploration into scalable, real-world applications. Communicate technical findings clearly to both specialized and cross-functional audiences. 4. Contribute to the Research Community Share findings through technical reports, publications, open-source work, workshops, or conference participation where appropriate. Contribute to Turing's research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community. What We're Looking For Research background: PhD or Master's degree in artificial intelligence, machine learning, computer science, or a closely related technical field; exceptional equivalent research experience will also be considered. Technical depth: Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling. Relevant expertise: Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks. Research engineering ability: Strong programming skills and the ability to implement, test, and iterate quickly in a research environment. Scientific judgment: Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making. Communication and collaboration: Clear written and verbal communication skills, intellectual curiosity, and the ability to work effectively across research and engineering teams. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents' ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. This role is required to be in office five days a week, based in any of Turing's offices in San Francisco, Palo Alto, or Seattle. Compensation: $250,000 to $400,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here.

Modal Window

  • Home
  • Contact
  • About Us
  • FAQs
  • Terms & Conditions
  • Privacy
  • Employer
  • Post a Job
  • Search Resumes
  • Sign in
  • Job Seeker
  • Find Jobs
  • Create Resume
  • Sign in
  • IT blog
  • Facebook
  • Twitter
  • LinkedIn
  • Youtube
© 2008-2026 IT Job Board