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Job Description Job Description Job Title: Machine Learning Operations Engineer Location: Dallas, Texas Type: Contract To Hire Compensation: $60.00 - $120,000.00 Work Model: Onsite - onsite Hours: 40.0 Security Clearance: None specified Overview Leave placeholder text here for recruiter to input Responsibilities Optimize and maintain large-scale feature engineering pipelines using PySpark, Pandas, and PyArrow on Hadoop-based infrastructure. Refactor and modularize ML codebases to enhance reusability, maintainability, and performance. Collaborate with platform teams on compute capacity planning, resource allocation, and system upgrades. Integrate with existing model serving frameworks to support testing, deployment, and rollback processes. Monitor and troubleshoot production ML pipelines, ensuring high reliability, low latency, and cost efficiency. Contribute to internal ML platforms by sharing insights, proposing improvements, and documenting best practices. Build near real-time ML pipelines using Kafka and Spark Streaming. Work with AWS and SageMaker MLOps ecosystem. Requirements 6+ years of experience in software engineering, data engineering, or MLOps roles. Strong programming expertise in Python, with hands-on experience in Pandas, PySpark, and PyArrow. Deep understanding of the Hadoop ecosystem, distributed computing, and performance tuning. Experience with CI/CD pipelines and best practices in ML environments. Hands-on experience with monitoring tools for ML pipeline health and performance. Strong collaboration skills with experience working in cross-functional teams (platform, data science, engineering). Experience contributing to or building internal MLOps frameworks/platforms. Familiarity with SLURM clusters or other distributed job schedulers. Exposure to Kafka, Spark Streaming, or other real-time data processing technologies. Understanding of ML lifecycle management, including versioning, deployment, and drift detection. System One, and its subsidiaries including Joulé and Mountain Ltd., are leaders in delivering outsourced services and workforce solutions across North America. We help clients get work done more efficiently and economically, without compromising quality. System One not only serves as a valued partner for our clients, but we offer eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans, as well as participation in a 401(k) plan. System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, age, national origin, disability, family care or medical leave status, genetic information, veteran status, marital status, or any other characteristic protected by applicable federal, state, or local law. Ref: Pittsburgh

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. If you will require McKesson to provide immigration support or sponsorship now or in the future, you should not apply for this position Ontada is seeking a highly motivated and hands-on Programmer/Analyst(P3) to support the design, development, and optimization of enterprise-scale healthcare data platforms. This role will play a critical part in building scalable data pipelines, modern analytics solutions, and cloud-based data engineering capabilities that power reporting, insights, and data-driven decision making across the organization. The ideal candidate combines deep technical expertise in Databricks, SQL, Python, and modern Business Intelligence platforms such as Power BI and Tableau with a strong understanding of healthcare data. This individual will collaborate closely with engineering, analytics, product, and business stakeholders to deliver reliable, high-performing, and scalable data solutions while ensuring compliance with healthcare data governance and regulatory requirements. Key Responsibilities Design, develop, and maintain scalable data pipelines using Databricks, Delta Lake, Apache Spark, SQL, and Python. Build and optimize ETL/ELT processes to support enterprise reporting, analytics, and operational data needs. Develop efficient data models and database solutions to enable high-performance analytics and business intelligence workloads. Partner with business stakeholders, product teams, and analytics teams to translate business requirements into scalable data solutions. Create and maintain dashboards, reports, and visualizations using Power BI and Tableau to provide actionable business insights. Ensure data quality, integrity, governance, and security across healthcare data platforms. Support ingestion, transformation, and integration of clinical, claims, provider, and patient datasets. Implement data validation, monitoring, and observability processes to ensure data reliability and operational excellence. Design and support workflow orchestration solutions using Databricks Workflows, Apache Airflow, or similar tools. Contribute to cloud-based data modernization initiatives and enterprise analytics platforms. Develop and maintain CI/CD pipelines and deployment processes utilizing GitHub and modern DevOps practices. Apply AI-assisted development tools to improve engineering productivity, code quality, testing, documentation, and overall delivery efficiency. Participate in Agile ceremonies including sprint planning, backlog refinement, estimation, and retrospectives. Troubleshoot complex data and performance issues and implement sustainable solutions. Collaborate effectively with cross-functional teams across engineering, architecture, product management, analytics, and operations. Minimum Requirement Degree or equivalent and typically requires 4+ years of relevant experience. Education Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience. Critical Skills 4+ years of experience in data engineering, database engineering, software engineering, or a related technical discipline. 3+ years of hands-on experience with SQL and relational database technologies. 2+ years of experience with Python development and automation. 2+ years of experience with Databricks, Spark, or modern cloud-based data engineering platforms. Experience with Power BI and/or Tableau. Experience working in Agile development environments. Experience using GitHub and CI/CD processes. Strong analytical, troubleshooting, and problem-solving capabilities. Technical Skills Data Engineering & Platform Technologies Strong hands-on experience with Databricks, including Delta Lake and Apache Spark. Advanced proficiency in SQL for complex queries, performance tuning, data modeling, and optimization. Strong programming expertise in Python for automation, data processing, integration, and analytics. Experience designing and maintaining enterprise-scale data pipelines and data processing frameworks. Experience with workflow orchestration platforms such as Databricks Workflows, Apache Airflow, or equivalent technologies. Reporting & Analytics Experience developing dashboards, reports, and visualizations using Power BI Ability to transform business requirements into actionable reporting and analytics solutions. Understanding of modern data warehousing, lakehouse architectures, and analytics best practices. DevOps & Software Engineering Strong knowledge of GitHub-based source control including branch protection policies, pull request reviews, release management, and version control best practices Experience implementing and maintaining CI/CD pipelines using GitHub Actions to automate build, testing, security validation, and deployment processes Familiarity with automated testing, deployment automation, and infrastructure best practices Experience working within Agile software development methodologies Healthcare Data Understanding of healthcare data domains, including: Clinical Data Claims Data Provider Data Patient Data Familiarity with HIPAA and healthcare compliance requirements. Understanding of healthcare data governance, privacy, and security best practices. AI-Assisted Development Experience leveraging AI development tools such as GitHub Copilot or equivalent solutions. Ability to utilize AI for code generation, optimization, testing, documentation, and productivity improvements. Preferred Qualifications Experience working in Azure cloud environments. Familiarity with Databricks, Delta Lake, Lakehouse architectures, and modern data platform design. Experience supporting large-scale healthcare analytics platforms. Experience with healthcare interoperability standards such as HL7 or FHIR. Experience implementing data quality frameworks and data observability solutions. Experience supporting enterprise reporting modernization initiatives. Exposure to machine learning, predictive analytics, or AI-enabled healthcare solutions. Core Attributes Exceptional problem-solving skills with the ability to troubleshoot and resolve complex technical and data-related challenges. Strong ownership mentality with a focus on accountability and delivering results. Naturally curious with a passion for continuous learning, innovation, and technology modernization. Excellent communication and collaboration skills across technical and non-technical stakeholders. Ability to work effectively in a fast-paced, data-driven, and highly collaborative environment. Strong attention to detail and commitment to delivering high-quality solutions. Demonstrates an enterprise mindset and a customer-first approach to decision-making. This position offers the possibility of a hybrid work arrangement based on recent updates to our in-office/work from home model. If located in DFW area, the selected candidate may be expected to work on site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in office days may be designated according to team needs and business priorities. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $111,800 - $186 . click apply for full job details

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. If you will require McKesson to provide immigration support or sponsorship now or in the future, you should not apply for this position Ontada is seeking a highly motivated and hands-on Programmer/Analyst(P3) to support the design, development, and optimization of enterprise-scale healthcare data platforms. This role will play a critical part in building scalable data pipelines, modern analytics solutions, and cloud-based data engineering capabilities that power reporting, insights, and data-driven decision making across the organization. The ideal candidate combines deep technical expertise in Databricks, SQL, Python, and modern Business Intelligence platforms such as Power BI and Tableau with a strong understanding of healthcare data. This individual will collaborate closely with engineering, analytics, product, and business stakeholders to deliver reliable, high-performing, and scalable data solutions while ensuring compliance with healthcare data governance and regulatory requirements. Key Responsibilities Design, develop, and maintain scalable data pipelines using Databricks, Delta Lake, Apache Spark, SQL, and Python. Build and optimize ETL/ELT processes to support enterprise reporting, analytics, and operational data needs. Develop efficient data models and database solutions to enable high-performance analytics and business intelligence workloads. Partner with business stakeholders, product teams, and analytics teams to translate business requirements into scalable data solutions. Create and maintain dashboards, reports, and visualizations using Power BI and Tableau to provide actionable business insights. Ensure data quality, integrity, governance, and security across healthcare data platforms. Support ingestion, transformation, and integration of clinical, claims, provider, and patient datasets. Implement data validation, monitoring, and observability processes to ensure data reliability and operational excellence. Design and support workflow orchestration solutions using Databricks Workflows, Apache Airflow, or similar tools. Contribute to cloud-based data modernization initiatives and enterprise analytics platforms. Develop and maintain CI/CD pipelines and deployment processes utilizing GitHub and modern DevOps practices. Apply AI-assisted development tools to improve engineering productivity, code quality, testing, documentation, and overall delivery efficiency. Participate in Agile ceremonies including sprint planning, backlog refinement, estimation, and retrospectives. Troubleshoot complex data and performance issues and implement sustainable solutions. Collaborate effectively with cross-functional teams across engineering, architecture, product management, analytics, and operations. Minimum Requirement Degree or equivalent and typically requires 4+ years of relevant experience. Education Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience. Critical Skills 4+ years of experience in data engineering, database engineering, software engineering, or a related technical discipline. 3+ years of hands-on experience with SQL and relational database technologies. 2+ years of experience with Python development and automation. 2+ years of experience with Databricks, Spark, or modern cloud-based data engineering platforms. Experience with Power BI and/or Tableau. Experience working in Agile development environments. Experience using GitHub and CI/CD processes. Strong analytical, troubleshooting, and problem-solving capabilities. Technical Skills Data Engineering & Platform Technologies Strong hands-on experience with Databricks, including Delta Lake and Apache Spark. Advanced proficiency in SQL for complex queries, performance tuning, data modeling, and optimization. Strong programming expertise in Python for automation, data processing, integration, and analytics. Experience designing and maintaining enterprise-scale data pipelines and data processing frameworks. Experience with workflow orchestration platforms such as Databricks Workflows, Apache Airflow, or equivalent technologies. Reporting & Analytics Experience developing dashboards, reports, and visualizations using Power BI Ability to transform business requirements into actionable reporting and analytics solutions. Understanding of modern data warehousing, lakehouse architectures, and analytics best practices. DevOps & Software Engineering Strong knowledge of GitHub-based source control including branch protection policies, pull request reviews, release management, and version control best practices Experience implementing and maintaining CI/CD pipelines using GitHub Actions to automate build, testing, security validation, and deployment processes Familiarity with automated testing, deployment automation, and infrastructure best practices Experience working within Agile software development methodologies Healthcare Data Understanding of healthcare data domains, including: Clinical Data Claims Data Provider Data Patient Data Familiarity with HIPAA and healthcare compliance requirements. Understanding of healthcare data governance, privacy, and security best practices. AI-Assisted Development Experience leveraging AI development tools such as GitHub Copilot or equivalent solutions. Ability to utilize AI for code generation, optimization, testing, documentation, and productivity improvements. Preferred Qualifications Experience working in Azure cloud environments. Familiarity with Databricks, Delta Lake, Lakehouse architectures, and modern data platform design. Experience supporting large-scale healthcare analytics platforms. Experience with healthcare interoperability standards such as HL7 or FHIR. Experience implementing data quality frameworks and data observability solutions. Experience supporting enterprise reporting modernization initiatives. Exposure to machine learning, predictive analytics, or AI-enabled healthcare solutions. Core Attributes Exceptional problem-solving skills with the ability to troubleshoot and resolve complex technical and data-related challenges. Strong ownership mentality with a focus on accountability and delivering results. Naturally curious with a passion for continuous learning, innovation, and technology modernization. Excellent communication and collaboration skills across technical and non-technical stakeholders. Ability to work effectively in a fast-paced, data-driven, and highly collaborative environment. Strong attention to detail and commitment to delivering high-quality solutions. Demonstrates an enterprise mindset and a customer-first approach to decision-making. This position offers the possibility of a hybrid work arrangement based on recent updates to our in-office/work from home model. If located in DFW area, the selected candidate may be expected to work on site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in office days may be designated according to team needs and business priorities. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $111,800 - $186 . click apply for full job details

IT Developer Company Overview Industry: Renewable Energy / Industrial Technology A technology-driven organization focused on innovation, operational excellence, and enterprise digital transformation. The company is investing in advanced data, analytics, and AI solutions to improve business performance and decision-making. Role Overview Position Title: IT Developer Location: Fully Remote Employment Type: Full Time Why is this role open? To support the development of enterprise applications, data solutions, system integrations, and analytics initiatives across the business. Job Description Overview Seeking an IT Developer to design, develop, and support enterprise applications and analytics solutions within a modern data platform environment. This role will focus on application development, data integration, workflow automation, reporting, and AI-enabled solutions that support operational and strategic business objectives. Key Responsibilities Design, develop, deploy, and maintain enterprise applications, workflows, and data products. Build and optimize data pipelines, integrations, and transformation processes. Develop dashboards, reporting solutions, and operational workflows. Collaborate with stakeholders to translate business requirements into technical solutions. Support AI-enabled applications, automation initiatives, and analytics solutions. Troubleshoot application, integration, and data quality issues. Perform testing, deployment, documentation, and ongoing support activities. Maintain data governance, security, and compliance standards. Partner with cross-functional business and technology teams. Create and maintain technical documentation and architecture artifacts. Business Impact This role helps drive digital transformation through improved data visibility, process automation, analytics, and operational efficiency across multiple business functions. Skills Required Skills Bachelor's degree in Computer Science, Information Technology, Information Systems, Software Engineering, Data Analytics, or a related field. 3+ years of experience in software development, application development, data engineering, or enterprise systems development. 2+ years of experience supporting enterprise data platforms, analytics solutions, or digital transformation initiatives. Experience developing integrations between enterprise applications and databases. Strong understanding of software development lifecycle (SDLC) methodologies. Experience with SQL and relational databases. Experience building APIs and system integrations. Understanding of cloud-based architectures and enterprise application design. Knowledge of data modeling, ETL processes, and data governance principles. Experience with Git, DevOps practices, and CI/CD pipelines. Strong troubleshooting, analytical, and problem-solving abilities. Excellent written and verbal communication skills. Ability to work effectively with both technical and non-technical stakeholders. Strong process improvement mindset and ability to manage multiple priorities in a fast-paced environment. Team-oriented approach to solution delivery. Preferred Skills Experience with enterprise data, analytics, or AI platforms. Experience with Python, Java, JavaScript, TypeScript, or similar programming languages. Experience supporting manufacturing, supply chain, industrial, or renewable energy operations. Familiarity with ERP systems such as SAP, Oracle, NetSuite, Microsoft Dynamics, or similar platforms. Experience developing AI, machine learning, predictive analytics, or workflow automation solutions. Experience with reporting and visualization tools. Knowledge of master data management and data governance best practices. Experience working in Agile/Scrum environments. Cultural Fit Collaborative and team-oriented Strong problem solver Continuous learner with interest in emerging technologies Adaptable in a fast-paced environment Business-focused and results-driven Determining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to the individual's skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law in geographies that require salary range disclosure, Vaco/Highspring notes the salary range for the role is noted in this job posting. The individual may also be eligible for discretionary bonuses, and can participate in medical, dental, and vision benefits as well as the company's 401(k) retirement plan. Additional disclaimer: Unless otherwise noted in the job description, the position Vaco/Highspring is filing for is occupied. Please note, however, that Vaco/Highspring is regularly asked to provide talent to other organizations. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. 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. Further assessment of candidates beyond this initial phase within Vaco/Highspring will be otherwise assessed by recruiters and hiring managers. Vaco/Highspring does not have knowledge of the tools used by its clients in making final hiring decisions and cannot opine on their use of AI products 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.

Vaco is partnering with a growing education technology organization to hire a Staff / Principal AI Engineer to help define and build the next generation of AI-powered products, platforms, and internal capabilities. This is a highly visible, hands-on technical leadership role focused on bringing practical AI innovation into both customer-facing products and internal business operations. This person will serve as a technical change leader as the organization moves toward broader use of AI agents, generative AI, machine learning, and LLM-powered product experiences. The right candidate will bring strong architecture and engineering depth, but also a product mindset. This role is about building real solutions, teaching teams how to use AI effectively, securing AI-enabled workflows, and identifying where AI can improve customer experience, training products, marketing funnels, and business outcomes. What You'll Be Doing Lead the design, development, and deployment of scalable AI and machine learning solutions across product and internal business use cases Architect generative AI systems, LLM-powered workflows, agentic solutions, and AI-enabled product features Build and optimize LLMOps pipelines that support reliable deployment, evaluation, monitoring, and iteration of AI models Partner with product, architecture, data, engineering, innovation, and marketing teams to identify where AI can create measurable business impact Drive AI innovation within customer-facing products, training platforms, digital experiences, and lead conversion workflows Evaluate and implement approaches for prompt engineering, context management, embeddings, retrieval, and model optimization Design AI systems with feedback loops, automated retraining, fine-tuning, and lifecycle management where appropriate Build data pipelines and preprocessing workflows that ensure data quality, security, and regulatory alignment Provide hands-on technical leadership through architecture reviews, code contributions, proof-of-concepts, and implementation guidance Mentor AI engineers and partner with architects across application, product, CRM, and data domains Help establish standards, documentation, and best practices for responsible AI development and deployment Stay current on emerging AI trends, including AI's impact on digital marketing, Answer Engine Optimization, Generative Engine Optimization, and customer discovery behavior Required Experience 8 or more years of progressive experience across software engineering, data, analytics, machine learning, AI engineering, or related technology roles 1 or more years of experience developing and implementing analytical, AI, or machine learning applications Hands-on experience building and deploying LLM-based solutions, generative AI applications, or AI-powered product features Strong understanding of machine learning, natural language processing, large language models, embeddings, retrieval patterns, and model evaluation Experience with Python, SQL, Hugging Face, Snowflake, and modern ML or analytics tooling Experience designing AI or ML solutions in Azure or comparable cloud environments Experience with CI/CD pipelines, Docker, Kubernetes, MLflow, or similar MLOps and lifecycle management tools Ability to translate ambiguous AI opportunities into practical, scalable engineering solutions Strong product mindset with interest in customer experience, product innovation, marketing enablement, and business impact Demonstrated ability to mentor engineers, influence technical direction, and guide best practices Strong communication skills with the ability to present complex AI concepts to technical and non-technical stakeholders Bachelor's degree in Computer Science, Artificial Intelligence, or a related field preferred, or equivalent professional experience Nice to Have Experience building AI agents or agentic workflows for internal business operations Exposure to AI security, responsible AI, model governance, or securing AI-enabled systems Experience applying AI to online shopping, customer acquisition, digital marketing, or lead conversion workflows Familiarity with Answer Engine Optimization or Generative Engine Optimization concepts Experience with Azure AI services or comparable cloud AI platforms Background working in education technology, training platforms, eCommerce, or digital learning environments Experience helping organizations adopt AI tools, workflows, and operating models across multiple teams Compensation & Benefits Salary range: $170,000 to $190,000 annually Full-time role with benefits package available If you are a hands-on AI engineering leader who wants to build practical generative AI systems, shape product innovation, and help an organization move from AI experimentation to real enterprise adoption, we would welcome the opportunity to connect. Determining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to the individual's skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law in geographies that require salary range disclosure, Vaco/Highspring notes the salary range for the role is noted in this job posting. The individual may also be eligible for discretionary bonuses, and can participate in medical, dental, and vision benefits as well as the company's 401(k) retirement plan. Additional disclaimer: Unless otherwise noted in the job description, the position Vaco/Highspring is filing for is occupied. Please note, however, that Vaco/Highspring is regularly asked to provide talent to other organizations. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. 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. Further assessment of candidates beyond this initial phase within Vaco/Highspring will be otherwise assessed by recruiters and hiring managers. Vaco/Highspring does not have knowledge of the tools used by its clients in making final hiring decisions and cannot opine on their use of AI products. 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 . click apply for full job details

About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Job Description Role Summary: We are seeking a talented and motivated Software Engineer to join our Payments Products development team. As a key member of the team, you will play a critical role in developing cutting-edge solutions, leveraging innovative technologies, and enhancing the capabilities of our platforms. You will be tasked to quickly grasp and evaluate new ideas and technologies from both internal and external sources and match them appropriately with emerging technology and business opportunities, building a culture of innovation and a drive for excellence. Essential Functions: Innovative Development: Engage in the design, development, and implementation of innovative software solutions, using generative AI and modern integration patterns. Contribute to a culture of innovation by actively exploring and applying new ideas and technologies. AI Solution Engineering: Support the implementation, fine-tuning, evaluation, integration, and deployment of AI components within enterprise applications, with attention to model robustness and operational quality. Collaborative Engineering: Collaborate with cross-functional teams to develop and deliver complex projects that integrate emerging technologies with our existing platforms. Work closely with Product Office, Operations & Infrastructure, Cybersecurity, Client Support, and other Product Development teams to build comprehensive solutions. Continuous Learning: Engage in continuous learning and development, actively seeking opportunities to enhance your skills and knowledge. Collaborate with peers to share insights and drive team growth. API and Integration Development: Contribute to the design and development of APIs that enhance the integration of our Payment Product applications, platforms, and solutions. Engineering Excellence: Adhere to industry best practices in software development, emphasizing quality, security, performance, scalability, availability, and resilience. Contribute to the management and reduction of technical debt within projects. Automation and Best Practices: Implement best engineering practices and automate software development, testing, and deployment processes. Ensure the timely delivery and maintenance of multiple services, focusing on continuous improvement. The Skills You Bring: Energy and Experience: A growth mindset that is curious and passionate about technologies and enjoys challenging projects on a global scale Challenge the Status Quo: Comfort in pushing the boundaries, hacking beyond traditional solutions Language Expertise: Expertise in one or more general development languages such as Java, Python, NodeJS, C#, or C++ AI Builder: Experience building, evaluating, integrating, and deploying Generative AI or machine learning capabilities within modern services and web applications Builder: Experience building and deploying modern services and web applications with quality and scalability Learner: Constant drive to learn new technologies such as GenAI, Angular, React, Kubernetes, Docker, and MLOps Partnership: Experience collaborating with Product, Test, DevOps, and Agile/Scrum teams Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: Bachelor's degree, OR 3+ years of relevant work experience. Expert-level skills in Java, Python, and/or NodeJS; skills in C++ and C# are a plus. Experience building Generative AI applications, conversational AI, RAG architectures, techniques, and libraries. Preferred Qualifications: Expertise in application security, SSDLC, and cryptography fundamentals. Self-driven and willing to work across technologies and languages. Understanding of NLP, including tokenization, word embeddings, and basic sequence models. Experience implementing and fine-tuning AI models using frameworks such as TensorFlow, PyTorch, or scikit-learn. Understanding of model compression techniques and related trade-offs. Awareness of transfer learning concepts and practical applications. Ability to design, implement, and integrate AI components into larger systems. Familiarity with common robustness issues in AI systems. Familiarity with machine learning and deep learning basics, including neural network architectures and training procedures. Exposure to machine learning operations (MLOps) and best practices for deploying AI and machine learning models. Experience with data preprocessing, feature engineering, and model evaluation techniques. Proficiency in front-end web development technologies such as ReactJS, Angular, and NodeJS. Ability to work with large datasets and perform exploratory data analysis. Expertise in multi-threading, concurrency, and error handling. Knowledge of version control, CI/CD pipelines, and best practices for deployments. Working knowledge of distributed in-memory computing technologies such as Redis. Information for US Applicants For roles located in the US, the estimated salary range for this position is $86,500 to $158,100 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.

About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters - to you, to your community, and to the world. Progress starts with you. Job Description The Opportunity We are seeking a talented and motivated Senior Software Development Engineer to join our Payments Products Development team. As a key member of the team, you will play a critical role in developing cutting-edge solutions, leveraging innovative technologies, and enhancing the capabilities of our platforms. You will quickly grasp and evaluate new ideas and technologies from internal and external sources, then match them to emerging technology and business opportunities while helping build a culture of innovation and engineering excellence. Essential Functions: AI-Enabled Innovative Development: Design, develop, and implement innovative software solutions using generative AI, conversational AI, RAG, and modern integration patterns. Explore new technologies and translate relevant ideas into secure, scalable business solutions. AI System Engineering: Design and integrate AI components into larger platforms, including data preparation, model evaluation, deployment, monitoring, and continuous improvement. Address robustness, quality, security, and operational reliability throughout the lifecycle. Collaborative Engineering: Collaborate with cross-functional teams to deliver complex projects that integrate emerging technologies with existing platforms. Work closely with Product Office, Operations & Infrastructure, Cybersecurity, Client Support, and Product Development teams. Continuous Learning: Actively expand knowledge of generative AI, machine learning, modern engineering practices, and emerging technologies. Share learning with peers and contribute to team growth. Client-Focused Solutions: Develop solutions with a client-centric mindset, ensuring Payment Product platforms deliver exceptional value and innovation. Use client feedback to refine and improve offerings. API and Integration Development: Contribute to the design and development of APIs that enhance integration across Payment Product applications, platforms, AI services, and solutions. Technology Modernization: Advance the modernization roadmap by adopting best-in-class technology solutions for core platforms, expanding market reach and client impact. Process Improvement: Continuously improve technology stacks, development processes, and methodologies to enhance productivity, quality, and time to market, including responsible use of AI-assisted engineering tools. Engineering Excellence: Follow industry best practices in software development, emphasizing quality, security, performance, scalability, availability, resilience, and reduction of technical debt. Automation and Best Practices: Automate software development, testing, deployment, and maintenance processes. Use AI-generated outputs as accelerators while applying rigorous engineering review and verification. Incident and Change Management: Support incident, change, and problem management processes. Participate in root-cause analysis and troubleshooting to sustain high availability and service reliability. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: 2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience Expert-level skills in Java, Python, and Node.js; experience with C++ or C# is a plus. Experience building Generative AI applications, conversational AI solutions, retrieval-augmented generation (RAG) architectures, and related techniques, tools, and libraries. Preferred Qualifications: 3 or more years of work experience with a Bachelor's Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) Self-driven, adaptable, and willing to work across technologies and programming languages. Strong understanding of natural language processing concepts, including tokenization, word embeddings, and sequence models. Proficiency implementing and fine-tuning AI and machine learning models using frameworks such as TensorFlow, PyTorch, or scikit-learn. Understanding of machine learning and deep learning fundamentals, including neural network architectures, training procedures, transfer learning, model compression, and associated trade-offs. Ability to design, implement, and integrate AI components into larger enterprise systems. Familiarity with common robustness, reliability, security, and responsible-use considerations in AI systems. Experience working with large datasets, exploratory data analysis, data preprocessing, feature engineering, and model evaluation techniques. Exposure to leading-edge areas such as machine learning, deep learning, stream computing, MLOps, and modern AI integration patterns. Proficiency in front-end web development technologies such as React, Angular, and Node.js. Experience configuring build and deployment systems such as Docker, Jenkins, and Kubernetes. Expertise in multithreading, concurrency, and error handling. Demonstrated proficiency in troubleshooting, root-cause analysis, application design, and implementing enterprise-scale components. Knowledge of version control, CI/CD pipelines, and best practices for application and ML model deployment. Working knowledge of distributed in-memory computing technologies such as Redis. Understanding of enterprise security, certificate management, and related practices. Hands-on experience with Jenkins and container deployment architecture. Experience with OAuth 2.0, SSO, and authentication methods or protocols. Expertise in application security, SSDLC, and cryptography fundamentals. Experience applying AI-assisted engineering practices while independently validating generated code, tests, documentation, and technical recommendations. Experience in the payments technology industry is a plus. The Skills You Bring: Energy and Experience: A growth mindset, curiosity about technology, and enthusiasm for challenging projects on a global scale. Challenge the Status Quo: Comfort pushing boundaries and exploring solutions beyond traditional approaches. Language Expertise: Expertise in one or more development languages such as Java, Python, Node.js, C#, or C++. AI Builder: Experience building and deploying Generative AI, conversational AI, RAG, machine learning, modern services, and web applications with quality and scalability. Critical AI Judgment: Ability to evaluate AI-generated code and recommendations, identify failure modes, and apply independent engineering judgment. Learner: A consistent drive to learn technologies such as GenAI, machine learning, Angular, React, Kubernetes, and Docker. Partnership: Experience collaborating with Product, Test, DevOps, Cybersecurity, and Agile/Scrum teams. Information for US Applicants For roles located in the US, the estimated salary range for this position is $112,100 to $204,000 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program. Work Hours Varies upon the needs of the department. Travel Requirements This position requires travel 5-10% of the time. Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers. Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color religion, sex, national origin, sexual orientation, gender identity, disability or protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. If you will require McKesson to provide immigration support or sponsorship now or in the future, you should not apply for this position Ontada is seeking a highly motivated and hands-on Programmer/Analyst(P3) to support the design, development, and optimization of enterprise-scale healthcare data platforms. This role will play a critical part in building scalable data pipelines, modern analytics solutions, and cloud-based data engineering capabilities that power reporting, insights, and data-driven decision making across the organization. The ideal candidate combines deep technical expertise in Databricks, SQL, Python, and modern Business Intelligence platforms such as Power BI and Tableau with a strong understanding of healthcare data. This individual will collaborate closely with engineering, analytics, product, and business stakeholders to deliver reliable, high-performing, and scalable data solutions while ensuring compliance with healthcare data governance and regulatory requirements. Key Responsibilities Design, develop, and maintain scalable data pipelines using Databricks, Delta Lake, Apache Spark, SQL, and Python. Build and optimize ETL/ELT processes to support enterprise reporting, analytics, and operational data needs. Develop efficient data models and database solutions to enable high-performance analytics and business intelligence workloads. Partner with business stakeholders, product teams, and analytics teams to translate business requirements into scalable data solutions. Create and maintain dashboards, reports, and visualizations using Power BI and Tableau to provide actionable business insights. Ensure data quality, integrity, governance, and security across healthcare data platforms. Support ingestion, transformation, and integration of clinical, claims, provider, and patient datasets. Implement data validation, monitoring, and observability processes to ensure data reliability and operational excellence. Design and support workflow orchestration solutions using Databricks Workflows, Apache Airflow, or similar tools. Contribute to cloud-based data modernization initiatives and enterprise analytics platforms. Develop and maintain CI/CD pipelines and deployment processes utilizing GitHub and modern DevOps practices. Apply AI-assisted development tools to improve engineering productivity, code quality, testing, documentation, and overall delivery efficiency. Participate in Agile ceremonies including sprint planning, backlog refinement, estimation, and retrospectives. Troubleshoot complex data and performance issues and implement sustainable solutions. Collaborate effectively with cross-functional teams across engineering, architecture, product management, analytics, and operations. Minimum Requirement Degree or equivalent and typically requires 4+ years of relevant experience. Education Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience. Critical Skills 4+ years of experience in data engineering, database engineering, software engineering, or a related technical discipline. 3+ years of hands-on experience with SQL and relational database technologies. 2+ years of experience with Python development and automation. 2+ years of experience with Databricks, Spark, or modern cloud-based data engineering platforms. Experience with Power BI and/or Tableau. Experience working in Agile development environments. Experience using GitHub and CI/CD processes. Strong analytical, troubleshooting, and problem-solving capabilities. Technical Skills Data Engineering & Platform Technologies Strong hands-on experience with Databricks, including Delta Lake and Apache Spark. Advanced proficiency in SQL for complex queries, performance tuning, data modeling, and optimization. Strong programming expertise in Python for automation, data processing, integration, and analytics. Experience designing and maintaining enterprise-scale data pipelines and data processing frameworks. Experience with workflow orchestration platforms such as Databricks Workflows, Apache Airflow, or equivalent technologies. Reporting & Analytics Experience developing dashboards, reports, and visualizations using Power BI Ability to transform business requirements into actionable reporting and analytics solutions. Understanding of modern data warehousing, lakehouse architectures, and analytics best practices. DevOps & Software Engineering Strong knowledge of GitHub-based source control including branch protection policies, pull request reviews, release management, and version control best practices Experience implementing and maintaining CI/CD pipelines using GitHub Actions to automate build, testing, security validation, and deployment processes Familiarity with automated testing, deployment automation, and infrastructure best practices Experience working within Agile software development methodologies Healthcare Data Understanding of healthcare data domains, including: Clinical Data Claims Data Provider Data Patient Data Familiarity with HIPAA and healthcare compliance requirements. Understanding of healthcare data governance, privacy, and security best practices. AI-Assisted Development Experience leveraging AI development tools such as GitHub Copilot or equivalent solutions. Ability to utilize AI for code generation, optimization, testing, documentation, and productivity improvements. Preferred Qualifications Experience working in Azure cloud environments. Familiarity with Databricks, Delta Lake, Lakehouse architectures, and modern data platform design. Experience supporting large-scale healthcare analytics platforms. Experience with healthcare interoperability standards such as HL7 or FHIR. Experience implementing data quality frameworks and data observability solutions. Experience supporting enterprise reporting modernization initiatives. Exposure to machine learning, predictive analytics, or AI-enabled healthcare solutions. Core Attributes Exceptional problem-solving skills with the ability to troubleshoot and resolve complex technical and data-related challenges. Strong ownership mentality with a focus on accountability and delivering results. Naturally curious with a passion for continuous learning, innovation, and technology modernization. Excellent communication and collaboration skills across technical and non-technical stakeholders. Ability to work effectively in a fast-paced, data-driven, and highly collaborative environment. Strong attention to detail and commitment to delivering high-quality solutions. Demonstrates an enterprise mindset and a customer-first approach to decision-making. This position offers the possibility of a hybrid work arrangement based on recent updates to our in-office/work from home model. If located in DFW area, the selected candidate may be expected to work on site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in office days may be designated according to team needs and business priorities. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $111,800 - $186 . click apply for full job details

Description : The Senior Manager, Commercial Analytics & Business Intelligence, is a pivotal, hands-on leader within the Commercial Operations function as DBV-Technologies prepares for its first U.S. commercial launch in Peanut Allergy. Reporting to the Head of Commercial Operations & Analytics, this individual will help design and build the commercial analytics engine from the ground up - the dashboards, data pipelines, KPIs, and insights that turn a first-launch biotech into a decision-ready organization. In a first-launch environment, analytics is not a back-office reporting function - it is a core strategic capability. Every targeting decision, segmentation model, incentive plan, and performance review depends on trustworthy data and sharp interpretation. This role sits at the intersection of business strategy, advanced analytics, and commercial execution, serving as a key partner to Marketing, Sales Leadership, Market Access, Forecasting, Finance, and Executive Leadership. The insights this individual produces will directly shape how the organization launches, learns, and refines its go-to-market model. The ideal candidate pairs deep technical fluency - advanced SQL, strong Python, modern BI, and applied AI - with the business acumen and executive communication skills to influence senior stakeholders without formal authority. This is deliberately not a reporting-only profile: we are looking for a builder who is equally comfortable architecting a data model, engineering an automated pipeline, and standing in front of leadership to tell the story the numbers reveal. Location : Warren, New Jersey - minimum 3 days on site Salary Range : $150-180k Key Responsibilities : Analytics, Reporting & Performance Management • Design, build, and maintain commercial analytics, reporting, dashboards, KPIs, and performance-management processes that give leadership a real-time view of launch performance against plan. • Develop KPI scorecards, trend analyses, and variance reporting for business performance reviews with senior leadership. • Translate complex, multi-source analyses into clear, actionable recommendations for executive decision-making. Data Sources & Commercial Insights • Develop insights from pharmaceutical patient, prescriber, claims, specialty pharmacy, hub, and market access data sources, integrating disparate feeds into coherent business narratives. • Build and maintain the analytical layer connecting Xponent, LAAD, claims, specialty pharmacy/hub, and payer data into usable, trustworthy assets. Launch Planning, Targeting & Field Effectiveness • Support launch planning through HCP-level targeting, segmentation, and call-plan analytics that focus field resources where they matter most. • Provide incentive compensation (IC) analytics and field force effectiveness measurement, quantifying the relationship between promotional activity and downstream prescribing. • Evaluate targeting and segmentation model performance post-launch and recommend refinements based on observed results. Forecasting, Finance & Scenario Analysis • Partner with Forecasting and Finance to evaluate business scenarios, performance drivers, and resource-allocation trade-offs. • Provide analytical support that connects performance data to budget cycles, long-range planning, and executive reporting. Data Governance & Best Practices • Drive data governance, documentation standards, and analytical best practices so the organization's data assets are reliable, compliant, and reusable. • Build scalable, automated pipelines and reporting to reduce manual effort and increase speed and accuracy. AI & Advanced Analytics • Identify high-value AI use cases and translate them into measurable business outcomes, applying LLMs, generative and agentic AI, and automation to improve commercial processes and decision-making. • Apply traditional machine learning and statistical methods (predictive modeling, segmentation, propensity) where they add commercial value. Qualifications : Required • 8-10 years of progressive experience in pharmaceutical analytics, commercial operations, business intelligence, or a closely related field. • Advanced SQL proficiency, with the ability to write, optimize, and maintain complex queries against large commercial datasets. • Strong Python skills for data engineering, automation, analytics, and predictive modeling. • Hands-on experience with BI and visualization platforms such as Power BI, Tableau, or similar tools. • Demonstrated experience with pharmaceutical commercial datasets, including IQVIA Xponent, IQVIA LAAD, claims data, specialty pharmacy and hub data, market access / payer data, and HCP-level targeting and segmentation datasets. • Demonstrated success supporting pharmaceutical product launches, including targeting, segmentation, IC analytics, and field force effectiveness. • Exceptional executive communication and storytelling skills, with a proven ability to influence cross-functional stakeholders without formal authority. • Comfort operating in a fast-paced, ambiguous, prelaunch environment, balancing strategic thinking with hands-on execution. • Bachelor's degree required, preferably in a quantitative discipline (Statistics, Economics, Mathematics, Engineering, Life Sciences, or related field). Preferred • Experience supporting specialty, immunology, allergy, rare disease, or biologic product launches. • Familiarity with cloud-based analytics environments and modern data architectures (e.g., AWS, Azure, Databricks, Snowflake). • Experience applying AI within commercial pharmaceutical organizations - including LLMs, generative AI, agentic AI, and automation tooling. • Experience with statistical analysis, predictive analytics, and data science methodologies. • Experience within emerging biotech companies or resource-constrained, high-growth environments. • Advanced degree (MBA, MS, or PhD) in a quantitative or business discipline. Behavioral skills : Curiosity: Keep on exploring uncharted territories. Always ask "why?" and more importantly "why not?", Courage: Take smart risks, mentor each other to always do better & be accountable for our choices, our opinions, and our actions, Collaboration: Teamwork and spirit. Support each other and be equally involved in the achievement of our common goals, Credibility: Be transparent, follow through and build trust. Educate ourselves about our unique technology.

Citizenship Requirement: Must be a U.S. Citizen Clearance Requirement: TS/SCI clearance with polygraph Job Duties Employ some combination (2 or more) of the following skill areas: Foundations: (Mathematical, Computational, Statistical) Data Processing: (Data management and curation, data description and visualization, workflow, and reproducibility) Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations) Devise strategies for extracting meaning and value from large datasets Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application-specific knowledge Through analytic modeling, statistical analysis, programming, and/or other appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in customer data holdings Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist other with drawing appropriate conclusions from the analysis of such data Effectively communicate complex technical information to non-technical audiences Make informed recommendations regarding competing technical solutions by maintaining awareness of constantly shifting collection, processing, storage and analytic capabilities and limitations Required Skills: US Citizens Only Active TS/SCI Clearance and Polygraph required Information Assurance Certification may be required Minimum of eight (8) years of relevant experience and a Master's degree; ten (10) years of relevant experience and a Bachelor's degree or 12 years of relevant experience and an Associate's degree required. Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university Relevant experience must be two of more of the following: Designing/implementing machine learning Data science Advanced analytical algorithms Programming (skill in at least one high-level language (e.g., Python Statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models) Data management (e.g., data cleaning and transformation) Data mining Data modeling and assessment Artificial intelligence Software engineering Compensation Range: $109,000 - $149,000 _ Compensation ranges encompass a total compensation package and are a general guideline only and not intended as a guaranteed and/or implied final compensation or salary for this job opening. Determination of official compensation or salary relies on several different factors including, but not limited to: level of position, complexity of job responsibilities, geographic location, candidate's scope of relevant work experience, educational background, certifications, contract-specific affordability, organizational requirements and alignment with local market data. Our compensation includes other indirect financial components designed to support employees' total well-being, which should be considered when evaluating our competitive benefits package. These monetary benefits include medical insurance, life insurance, disability, paid time off, maternity/paternity leave, 401(k) company match, training/education reimbursements and other work/life programs. _ IntelliGenesis is committed to providing equal opportunity to all employees and applicants for employment. The Company is an Equal Opportunity Employer (EOE), and as such, does not tolerate discrimination, retaliation, or harassment of its employees or applicants based upon race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or any other protected characteristic under local, state, or federal law in any employment practice. Such employment practices include, but are not limited to: hiring, promotion, demotion, transfer, recruitment, or recruitment advertising, selection, disciplinary action layoff, termination, rates of pay, or other forms of compensation and selection of training. IntelliGenesis is committed to the fair and equal employment of individuals with disabilities. It is the Company's policy to reasonably accommodate qualified individuals with disabilities unless the accommodation would impose an undue hardship on the organization. In accordance with the Americans with Disabilities Act (ADA) as amended, reasonable accommodations will be provided to qualified individuals with disabilities, when such accommodations are necessary, to enable them to perform the essential functions of their jobs or to enjoy the equal benefits and privileges of employment. This policy applies to all applicants for employment and all employees.

Citizenship Requirement: Must be a U.S. Citizen Clearance Requirement: TS/SCI clearance with polygraph Job Duties Employ some combination (2 or more) of the following skill areas: Foundations: (Mathematical, Computational, Statistical) Data Processing: (Data management and curation, data description and visualization, workflow, and reproducibility) Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations) Devise strategies for extracting meaning and value from large datasets Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application-specific knowledge Through analytic modeling, statistical analysis, programming, and/or other appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in customer data holdings Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist other with drawing appropriate conclusions from the analysis of such data Effectively communicate complex technical information to non-technical audiences Make informed recommendations regarding competing technical solutions by maintaining awareness of constantly shifting collection, processing, storage and analytic capabilities and limitations Required Skills: US Citizens Only Active TS/SCI Clearance and Polygraph required Information Assurance Certification may be required Minimum of three (3) years of relevant experience and a Bachelor's degree or five (5) years of relevant experience and an Associate's degree required. Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university Relevant experience must be two of more of the following: Designing/implementing machine learning Data science Advanced analytical algorithms Programming (skill in at least one high-level language (e.g., Python Statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models) Data management (e.g., data cleaning and transformation) Data mining Data modeling and assessment Artificial intelligence Software engineering Compensation Range: $43,000 - $95,000 _ Compensation ranges encompass a total compensation package and are a general guideline only and not intended as a guaranteed and/or implied final compensation or salary for this job opening. Determination of official compensation or salary relies on several different factors including, but not limited to: level of position, complexity of job responsibilities, geographic location, candidate's scope of relevant work experience, educational background, certifications, contract-specific affordability, organizational requirements and alignment with local market data. Our compensation includes other indirect financial components designed to support employees' total well-being, which should be considered when evaluating our competitive benefits package. These monetary benefits include medical insurance, life insurance, disability, paid time off, maternity/paternity leave, 401(k) company match, training/education reimbursements and other work/life programs. _ IntelliGenesis is committed to providing equal opportunity to all employees and applicants for employment. The Company is an Equal Opportunity Employer (EOE), and as such, does not tolerate discrimination, retaliation, or harassment of its employees or applicants based upon race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or any other protected characteristic under local, state, or federal law in any employment practice. Such employment practices include, but are not limited to: hiring, promotion, demotion, transfer, recruitment, or recruitment advertising, selection, disciplinary action layoff, termination, rates of pay, or other forms of compensation and selection of training. IntelliGenesis is committed to the fair and equal employment of individuals with disabilities. It is the Company's policy to reasonably accommodate qualified individuals with disabilities unless the accommodation would impose an undue hardship on the organization. In accordance with the Americans with Disabilities Act (ADA) as amended, reasonable accommodations will be provided to qualified individuals with disabilities, when such accommodations are necessary, to enable them to perform the essential functions of their jobs or to enjoy the equal benefits and privileges of employment. This policy applies to all applicants for employment and all employees.

Citizenship Requirement: Must be U.S. Citizen Clearance Requirement: TS/SCI clearance with polygraph Job Duties Employ some combination (2 or more) of the following skill areas: Foundations: (Mathematical, Computational, Statistical) Data Processing: (Data management and curation, data description and visualization, workflow, and reproducibility) Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations) Devise strategies for extracting meaning and value from large datasets Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application-specific knowledge Through analytic modeling, statistical analysis, programming, and/or other appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in customer data holdings Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist other with drawing appropriate conclusions from the analysis of such data Effectively communicate complex technical information to non-technical audiences Make informed recommendations regarding competing technical solutions by maintaining awareness of constantly shifting collection, processing, storage and analytic capabilities and limitations Required Skills: US Citizens Only Active TS/SCI Clearance and Polygraph required Information Assurance Certification may be required Minimum of three (3) years of relevant experience and a Bachelor's degree or five (5) years of relevant experience and an Associate's degree required. Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university Relevant experience must be two of more of the following: Designing/implementing machine learning Data science Advanced analytical algorithms Programming (skill in at least one high-level language (e.g., Python Statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models) Data management (e.g., data cleaning and transformation) Data mining Data modeling and assessment Artificial intelligence Software engineering Compensation Range: $85,000 - $116,000 _ Compensation ranges encompass a total compensation package and are a general guideline only and not intended as a guaranteed and/or implied final compensation or salary for this job opening. Determination of official compensation or salary relies on several different factors including, but not limited to: level of position, complexity of job responsibilities, geographic location, candidate's scope of relevant work experience, educational background, certifications, contract-specific affordability, organizational requirements and alignment with local market data. Our compensation includes other indirect financial components designed to support employees' total well-being, which should be considered when evaluating our competitive benefits package. These monetary benefits include medical insurance, life insurance, disability, paid time off, maternity/paternity leave, 401(k) company match, training/education reimbursements and other work/life programs. _ IntelliGenesis is committed to providing equal opportunity to all employees and applicants for employment. The Company is an Equal Opportunity Employer (EOE), and as such, does not tolerate discrimination, retaliation, or harassment of its employees or applicants based upon race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or any other protected characteristic under local, state, or federal law in any employment practice. Such employment practices include, but are not limited to: hiring, promotion, demotion, transfer, recruitment, or recruitment advertising, selection, disciplinary action layoff, termination, rates of pay, or other forms of compensation and selection of training. IntelliGenesis is committed to the fair and equal employment of individuals with disabilities. It is the Company's policy to reasonably accommodate qualified individuals with disabilities unless the accommodation would impose an undue hardship on the organization. In accordance with the Americans with Disabilities Act (ADA) as amended, reasonable accommodations will be provided to qualified individuals with disabilities, when such accommodations are necessary, to enable them to perform the essential functions of their jobs or to enjoy the equal benefits and privileges of employment. This policy applies to all applicants for employment and all employees.

Citizenship Requirement: Must be a U.S. Citizen Clearance Requirement: TS/SCI clearance with polygraph Job Description: IntelliGenesis is seeking a Senior AI Engineer to lead the design, development, and deployment of production-grade AI systems supporting mission-critical intelligence operations. This role focuses on transitioning AI/ML capabilities from concept to operational environments, including classified and resource-constrained settings. A day in the life includes architecting scalable AI pipelines, deploying models to edge and cloud environments, integrating AI into cybersecurity workflows, and mentoring junior engineers. You will work closely with cyber operators, software engineers, and infrastructure teams to deliver impactful, real-world AI capabilities-not just research prototypes. The team dynamic is highly collaborative and mission-driven, consisting of AI engineers, cyber SMEs, and platform engineers working in agile sprints. This role serves as a technical leader and mentor, guiding best practices in MLOps, DevSecOps, and secure AI deployment. Lead end-to-end AI system design, development, and deployment Architect and implement scalable MLOps pipelines for training, validation, and deployment Deploy AI/ML models to cloud, on-prem, and edge environments Integrate AI capabilities into cybersecurity tools and operational workflows Ensure system security, including adversarial robustness and secure model deployment Collaborate with cross-functional teams (cyber, infrastructure, software engineering) Mentor mid-level engineers and provide technical oversight Rapidly prototype AI solutions and transition them into production systems Ensure compliance with DoD Risk Management Framework (RMF) requirements Required Qualifications: Must be a U.S. Citizen Active TS/SCI Clearance and Polygraph required 8+ years of experience in AI/ML engineering, software engineering, or related field Bachelor's degree in Computer Science, Engineering, or related field Strong experience deploying AI/ML models into production environments Expertise in Python and at least one additional language (e.g., C++, Go) Experience with MLOps tools (e.g., Kubernetes, Docker, MLflow, Kubeflow, VMWare, Tanzu) Experience with cloud and hybrid infrastructure (AWS, Azure, or DoD cloud environments) Knowledge of DevSecOps and infrastructure-as-code (e.g., Terraform, Ansible) Experience with model serving, monitoring, and lifecycle management Familiarity with cybersecurity concepts and secure system design Experience working in classified or regulated environments (DoD/IC preferred) Desired Qualifications: Master's degree Experience with adversarial machine learning and AI security Background in cyber operations or network traffic analysis Experience deploying models in edge or disconnected environments Familiarity with large language models (LLMs) and generative AI systems Knowledge of secure enclaves and confidential computing Prior experience supporting DoD or Intelligence Community missions Relevant certifications (e.g., AWS Certified Solutions Architect, Security+, CISSP) Compensation Range: $215,000 - $245,000 _ Compensation ranges encompass a total compensation package and are a general guideline only and not intended as a guaranteed and/or implied final compensation or salary for this job opening. Determination of official compensation or salary relies on several different factors including, but not limited to: level of position, complexity of job responsibilities, geographic location, candidate's scope of relevant work experience, educational background, certifications, contract-specific affordability, organizational requirements and alignment with local market data. Our compensation includes other indirect financial components designed to support employees' total well-being, which should be considered when evaluating our competitive benefits package. These monetary benefits include medical insurance, life insurance, disability, paid time off, maternity/paternity leave, 401(k) company match, training/education reimbursements and other work/life programs. _ IntelliGenesis is committed to providing equal opportunity to all employees and applicants for employment. The Company is an Equal Opportunity Employer (EOE), and as such, does not tolerate discrimination, retaliation, or harassment of its employees or applicants based upon race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or any other protected characteristic under local, state, or federal law in any employment practice. Such employment practices include, but are not limited to: hiring, promotion, demotion, transfer, recruitment, or recruitment advertising, selection, disciplinary action layoff, termination, rates of pay, or other forms of compensation and selection of training. IntelliGenesis is committed to the fair and equal employment of individuals with disabilities. It is the Company's policy to reasonably accommodate qualified individuals with disabilities unless the accommodation would impose an undue hardship on the organization. In accordance with the Americans with Disabilities Act (ADA) as amended, reasonable accommodations will be provided to qualified individuals with disabilities, when such accommodations are necessary, to enable them to perform the essential functions of their jobs or to enjoy the equal benefits and privileges of employment. This policy applies to all applicants for employment and all employees.

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.

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.

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.

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 Senior 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 $350,000 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.

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 Senior 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 $350,000 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.

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 Senior 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 $350,000 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.

About the Role The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition to that, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems. As a Platform Engineer in Model Shaping, you will work at the intersection of backend engineering and infrastructure, building the foundational layers of Together's platform for model customization and evaluation. You will design, develop, and operate both the backend services and the underlying systems that enable us to sustainably and reliably scale production workflows launched by our users, as well as internal research experiments. You will operate in a cross-functional environment, collaborating with other engineers and researchers in the team to improve the infrastructure based on the needs of projects they work on. You will also interact with other engineering teams at Together (such as Commerce, Data Engineering, and Cloud Infrastructure) to integrate the services developed by Model Shaping with systems developed by those teams. Responsibilities Design and build Together's systems and infrastructure for model customization, including user-facing features and internal improvements Contribute to reliability improvements for the platform, participating in an on-call rotation and improving processes for incident response Create and improve internal tooling for deployment, continuous integration, and observability Build a job orchestration platform spanning multiple datacenters, supporting a highly heterogeneous hardware landscape Partner with teams developing internal services, co-designing these services and incorporating them in systems built within Together Requirements 3+ years of experience in building infrastructure or backend components of production services Extensive experience designing, operating, and troubleshooting production Linux environments and Kubernetes-based platforms Strong software engineering background in Python or Go Experienced with infrastructure automation tools (Terraform, Ansible), monitoring/observability stacks (Prometheus, Grafana), and CI/CD pipelines (GitHub Actions, ArgoCD) Cloud environment (e.g., AWS/GCP/Azure) administration experience, preferably with a hybrid bare-metal/cloud environment Strong communication skills, be willing to document systems and processes and collaborate with peers of varying technical expertise Comfortable operating across the stack, from cluster operations and infrastructure automation to backend service development Experience in any of the following will make you stand out: Developing large-scale production systems with high reliability requirements Pipeline orchestration frameworks (e.g., Kubeflow, Argo Workflows, Flyte) Managing GPU workloads on HPC clusters, ideally with hands-on experience in operating NVIDIA's networking stack (e.g., NCCL, Mellanox firmware, GPUDirect RDMA) Deployment of services for AI training or inference Networking fundamentals, including TCP/IP, DNS, routing, load balancing, TLS, and network debugging tools Maintaining or contributing to open-source projects About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is $200,000 - $290,000. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at