We are seeking an accomplished Chief Technology Officer, CTO to lead the technology vision, engineering organization, AI strategy, and product architecture for a growing enterprise SaaS company serving Fortune 500 customers. The ideal candidate is a strategic, hands-on technology executive with a proven track record of scaling high-performing engineering organizations and delivering innovative, AI-enabled software solutions. Key Qualifications Prior Sr. Principal Architect or CTO-level technical leader 812 years in modern SaaS (not necessarily 25+ years) Built 3+ successful SaaS products Personally shipped AI into production code (not just AI strategy or governance) Deep understanding of: Tokenization/token costs Model selection (GPT, Claude, Gemini, open-source models) Prompt engineering RAG Vector databases AI agents/MCP Experience with SMB, dealer networks, or marketing services is a plus. Experience with MarTech, Through-Channel Marketing Automation (TCMA), Co-op Fund Management, Market Development Funds (MDF), SPIFFs, Partner Relationship Management (PRM), incentives, rebates, and channel marketing solutions is highly desirable. Excellent executive leadership, communication, and cross-functional collaboration skills. Education Bachelor's degree in Computer Science, Engineering, or a related technical discipline required. Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field preferred. Compensation We offer a highly competitive compensation package that includes a market-based base salary , an attractive performance bonus , and the opportunity to participate in a long-term equity incentive program (link removed) Compensation will be commensurate with experience, leadership capability, and technical expertise.
08/06/2026
We are seeking an accomplished Chief Technology Officer, CTO to lead the technology vision, engineering organization, AI strategy, and product architecture for a growing enterprise SaaS company serving Fortune 500 customers. The ideal candidate is a strategic, hands-on technology executive with a proven track record of scaling high-performing engineering organizations and delivering innovative, AI-enabled software solutions. Key Qualifications Prior Sr. Principal Architect or CTO-level technical leader 812 years in modern SaaS (not necessarily 25+ years) Built 3+ successful SaaS products Personally shipped AI into production code (not just AI strategy or governance) Deep understanding of: Tokenization/token costs Model selection (GPT, Claude, Gemini, open-source models) Prompt engineering RAG Vector databases AI agents/MCP Experience with SMB, dealer networks, or marketing services is a plus. Experience with MarTech, Through-Channel Marketing Automation (TCMA), Co-op Fund Management, Market Development Funds (MDF), SPIFFs, Partner Relationship Management (PRM), incentives, rebates, and channel marketing solutions is highly desirable. Excellent executive leadership, communication, and cross-functional collaboration skills. Education Bachelor's degree in Computer Science, Engineering, or a related technical discipline required. Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field preferred. Compensation We offer a highly competitive compensation package that includes a market-based base salary , an attractive performance bonus , and the opportunity to participate in a long-term equity incentive program (link removed) Compensation will be commensurate with experience, leadership capability, and technical expertise.
We are seeking an accomplished Chief Technology Officer, CTO to lead the technology vision, engineering organization, AI strategy, and product architecture for a growing enterprise SaaS company serving Fortune 500 customers. The ideal candidate is a strategic, hands-on technology executive with a proven track record of scaling high-performing engineering organizations and delivering innovative, AI-enabled software solutions. Key Qualifications Prior Sr. Principal Architect or CTO-level technical leader 812 years in modern SaaS (not necessarily 25+ years) Built 3+ successful SaaS products Personally shipped AI into production code (not just AI strategy or governance) Deep understanding of: Tokenization/token costs Model selection (GPT, Claude, Gemini, open-source models) Prompt engineering RAG Vector databases AI agents/MCP Experience with SMB, dealer networks, or marketing services is a plus. Experience with MarTech, Through-Channel Marketing Automation (TCMA), Co-op Fund Management, Market Development Funds (MDF), SPIFFs, Partner Relationship Management (PRM), incentives, rebates, and channel marketing solutions is highly desirable. Excellent executive leadership, communication, and cross-functional collaboration skills. Education Bachelor's degree in Computer Science, Engineering, or a related technical discipline required. Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field preferred. Compensation We offer a highly competitive compensation package that includes a market-based base salary , an attractive performance bonus , and the opportunity to participate in a long-term equity incentive program (link removed) Compensation will be commensurate with experience, leadership capability, and technical expertise.
08/06/2026
We are seeking an accomplished Chief Technology Officer, CTO to lead the technology vision, engineering organization, AI strategy, and product architecture for a growing enterprise SaaS company serving Fortune 500 customers. The ideal candidate is a strategic, hands-on technology executive with a proven track record of scaling high-performing engineering organizations and delivering innovative, AI-enabled software solutions. Key Qualifications Prior Sr. Principal Architect or CTO-level technical leader 812 years in modern SaaS (not necessarily 25+ years) Built 3+ successful SaaS products Personally shipped AI into production code (not just AI strategy or governance) Deep understanding of: Tokenization/token costs Model selection (GPT, Claude, Gemini, open-source models) Prompt engineering RAG Vector databases AI agents/MCP Experience with SMB, dealer networks, or marketing services is a plus. Experience with MarTech, Through-Channel Marketing Automation (TCMA), Co-op Fund Management, Market Development Funds (MDF), SPIFFs, Partner Relationship Management (PRM), incentives, rebates, and channel marketing solutions is highly desirable. Excellent executive leadership, communication, and cross-functional collaboration skills. Education Bachelor's degree in Computer Science, Engineering, or a related technical discipline required. Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field preferred. Compensation We offer a highly competitive compensation package that includes a market-based base salary , an attractive performance bonus , and the opportunity to participate in a long-term equity incentive program (link removed) Compensation will be commensurate with experience, leadership capability, and technical expertise.
Kaiser Permanente seeks an IT Infrastructure Engineer V to design, implement, and optimize secure, scalable infrastructure supporting enterprise healthcare systems. In this senior role, you'll architect hybrid cloud and on prem environments, lead complex migrations, and drive automation using Infrastructure as Code to improve reliability and speed. You'll collaborate with security, application, and operations teams to ensure high availability, robust monitoring, and disaster recovery. This position offers growth, technical leadership opportunities, and impact on mission-critical patient care systems within a collaborative, innovation-focused culture.
08/06/2026
Full time
Kaiser Permanente seeks an IT Infrastructure Engineer V to design, implement, and optimize secure, scalable infrastructure supporting enterprise healthcare systems. In this senior role, you'll architect hybrid cloud and on prem environments, lead complex migrations, and drive automation using Infrastructure as Code to improve reliability and speed. You'll collaborate with security, application, and operations teams to ensure high availability, robust monitoring, and disaster recovery. This position offers growth, technical leadership opportunities, and impact on mission-critical patient care systems within a collaborative, innovation-focused culture.
Kaiser Permanente seeks a Principal IT Infrastructure Engineer to lead the design, implementation, and optimization of secure, scalable infrastructure supporting critical healthcare systems. You will architect hybrid cloud and on-prem solutions, drive automation with Infrastructure as Code, and ensure high availability, performance, and resilience. Partnering with cross-functional teams, you'll guide standards, mentor engineers, and champion observability, security, and reliability. Join a collaborative, innovation-focused culture that supports continuous learning and offers meaningful impact on patient care and operational excellence.
08/06/2026
Full time
Kaiser Permanente seeks a Principal IT Infrastructure Engineer to lead the design, implementation, and optimization of secure, scalable infrastructure supporting critical healthcare systems. You will architect hybrid cloud and on-prem solutions, drive automation with Infrastructure as Code, and ensure high availability, performance, and resilience. Partnering with cross-functional teams, you'll guide standards, mentor engineers, and champion observability, security, and reliability. Join a collaborative, innovation-focused culture that supports continuous learning and offers meaningful impact on patient care and operational excellence.
Lead Machine Learning Engineer (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
08/06/2026
Full time
Lead Machine Learning Engineer (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Description: This position will assist the department process engineers and supervisors, and plant management in ensuring the efficiency and effectiveness of all improvement aspects within the electrical and process automation systems. The major role of this job is to focus on continuous improvement and integration of improvement principles, technical and engineering principles, identifying best practices, and act as a change agent to help achieve a higher level of results within the assigned location by maximizing existing technologies and implementing new solutions to processes. This position serves in a material manufacturing automated processes advisory capacity with no direct reports. Serves as a coach to all production and maintenance employees, and plant management. Primary responsibility and accountability rests with higher levels of supervision. Requirements: The major role of this job is to identify opportunities for improvement in processes, products, and production within the electrical and process automation systems. These duties will include the development and implementation of new as well as adjusting existing standards, structures, systems, and equipment. This position is responsible to ensure the efficiency and effectiveness of all improvement aspects within their area of responsibility. Incumbent will be responsible for reaching improvement through the application of the available methods and tools in conjunction with the use of technical and engineering principles. Responsible for coordinating improvement activities directly with the appropriate Superintendent, Supervisors, and staff within the steelmaking process area. Qualifications for this position include a four year college degree in Engineering (Electrical or Electronic preferably) combined with 5 or more years experience in an industrial or manufacturing environment with high level exposure to advanced process and factory automation technologies, standardization and production quality methods. Incumbent must have an extensive knowledge of steel manufacturing methods, techniques and technologies involving the use of heavy mill machinery and related equipment. Previous qualifying experience in scrap processing, melting, casting, rolling, maintenance, finishing, shipping/warehouse operations, and supervisory/facilitation a must. Successful candidate will demonstrate an extensive knowledge of the business system and the use of complex technical and engineering processes. Requires the ability to train people and serve as a coach to employees. The incumbent should possess solid presentation abilities combined with good interpersonal and organizational skills. This position directly reports to the Department Manager. The incumbent will coordinate efforts with the different functional groups both within area of responsibility and other areas of the location. The incumbent would be detail oriented, self-driven and must be comfortable dealing with associates at all levels within the organization. The incumbent will be responsible for the oversight, contribution to, and support of all the automation technologies trainings and development activities for employees of the location. PM19 PI17197bbbcd28-9928
08/06/2026
Full time
Description: This position will assist the department process engineers and supervisors, and plant management in ensuring the efficiency and effectiveness of all improvement aspects within the electrical and process automation systems. The major role of this job is to focus on continuous improvement and integration of improvement principles, technical and engineering principles, identifying best practices, and act as a change agent to help achieve a higher level of results within the assigned location by maximizing existing technologies and implementing new solutions to processes. This position serves in a material manufacturing automated processes advisory capacity with no direct reports. Serves as a coach to all production and maintenance employees, and plant management. Primary responsibility and accountability rests with higher levels of supervision. Requirements: The major role of this job is to identify opportunities for improvement in processes, products, and production within the electrical and process automation systems. These duties will include the development and implementation of new as well as adjusting existing standards, structures, systems, and equipment. This position is responsible to ensure the efficiency and effectiveness of all improvement aspects within their area of responsibility. Incumbent will be responsible for reaching improvement through the application of the available methods and tools in conjunction with the use of technical and engineering principles. Responsible for coordinating improvement activities directly with the appropriate Superintendent, Supervisors, and staff within the steelmaking process area. Qualifications for this position include a four year college degree in Engineering (Electrical or Electronic preferably) combined with 5 or more years experience in an industrial or manufacturing environment with high level exposure to advanced process and factory automation technologies, standardization and production quality methods. Incumbent must have an extensive knowledge of steel manufacturing methods, techniques and technologies involving the use of heavy mill machinery and related equipment. Previous qualifying experience in scrap processing, melting, casting, rolling, maintenance, finishing, shipping/warehouse operations, and supervisory/facilitation a must. Successful candidate will demonstrate an extensive knowledge of the business system and the use of complex technical and engineering processes. Requires the ability to train people and serve as a coach to employees. The incumbent should possess solid presentation abilities combined with good interpersonal and organizational skills. This position directly reports to the Department Manager. The incumbent will coordinate efforts with the different functional groups both within area of responsibility and other areas of the location. The incumbent would be detail oriented, self-driven and must be comfortable dealing with associates at all levels within the organization. The incumbent will be responsible for the oversight, contribution to, and support of all the automation technologies trainings and development activities for employees of the location. PM19 PI17197bbbcd28-9928
Position: Senior Security Engineer - PKI & Detection, Aircraft Security Location: Fort Worth Texas (Hybrid - onsite Tuesday through Thursday; remote Monday and Friday) Duration: Contract Job ID: 178661 Job Overview: We are seeking a Senior Security Engineer to support aircraft security initiatives focused on detection, remediation, and Public Key Infrastructure (PKI). This role will independently design and operate security solutions, investigate security events, develop detections, and drive remediation activities through validated closure. The ideal candidate brings strong hands-on PKI engineering expertise, Microsoft Sentinel detection engineering experience, and the ability to work across technical teams to improve security, reliability, and scalability. Responsibilities: Design, build, test, document, and maintain security engineering solutions, scripts, processes, and reusable components in accordance with organizational standards. Develop and tune Microsoft Sentinel detections, KQL queries, analytics rules, dashboards, and investigation workflows. Conduct end-to-end security event investigations, perform root-cause analysis, and produce clear written documentation of findings and corrective actions. Own remediation lifecycle activities, including remediation-plan reviews, vulnerability and finding tracking, and validation of closure. Design and operate PKI solutions, including certificate enrollment, authentication, software signing, validation, and supporting key-management processes. Partner with security and engineering teams to incorporate security-conscious practices early in the system development lifecycle. Identify technical risks related to scalability, latency, durability, and security, and lead practical mitigation strategies. Guide junior engineers on technical craftsmanship and contribute to continuous improvement of engineering practices. Explore emerging technologies and develop prototypes that may be incorporated into security architecture and operational solutions. Qualifications: At least 5 years of security engineering experience with demonstrated independent project ownership; queue-based SOC or triage-only experience is not sufficient. Hands-on PKI engineering experience, including PKI solution design and operations, certificate enrollment protocols such as SCEP and EST, Certificate Policy/Certification Practice Statements (CP/CPS), trusted roles, Levels of Assurance, and NIST SP 800-63. Strong Microsoft Sentinel experience, including KQL/query development, detection rule authoring, dashboard development, and independently led end-to-end security event investigations. Experience owning remediation lifecycle engineering, including remediation-plan review, vulnerability/finding tracking, and validated closure. Nice to Have Skills and Experience: Experience with AI or agentic security tooling, including LLM-assisted code or configuration analysis and prompt engineering for security use cases. Endpoint platform engineering, SSO policy groups, API scripting and automation using Python or PowerShell. Experience with aviation, OT, cyber-physical systems, embedded systems, HSMs, key-management, or code-signing infrastructure. Interview Process: Two interview rounds: the first interview will be virtual, followed by an in-person interview. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $60-$65/Hr on W2 The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global, do not respond or click on any links. Instead, contact us directly at +1 . To report any concerns, please email us at
08/06/2026
Full time
Position: Senior Security Engineer - PKI & Detection, Aircraft Security Location: Fort Worth Texas (Hybrid - onsite Tuesday through Thursday; remote Monday and Friday) Duration: Contract Job ID: 178661 Job Overview: We are seeking a Senior Security Engineer to support aircraft security initiatives focused on detection, remediation, and Public Key Infrastructure (PKI). This role will independently design and operate security solutions, investigate security events, develop detections, and drive remediation activities through validated closure. The ideal candidate brings strong hands-on PKI engineering expertise, Microsoft Sentinel detection engineering experience, and the ability to work across technical teams to improve security, reliability, and scalability. Responsibilities: Design, build, test, document, and maintain security engineering solutions, scripts, processes, and reusable components in accordance with organizational standards. Develop and tune Microsoft Sentinel detections, KQL queries, analytics rules, dashboards, and investigation workflows. Conduct end-to-end security event investigations, perform root-cause analysis, and produce clear written documentation of findings and corrective actions. Own remediation lifecycle activities, including remediation-plan reviews, vulnerability and finding tracking, and validation of closure. Design and operate PKI solutions, including certificate enrollment, authentication, software signing, validation, and supporting key-management processes. Partner with security and engineering teams to incorporate security-conscious practices early in the system development lifecycle. Identify technical risks related to scalability, latency, durability, and security, and lead practical mitigation strategies. Guide junior engineers on technical craftsmanship and contribute to continuous improvement of engineering practices. Explore emerging technologies and develop prototypes that may be incorporated into security architecture and operational solutions. Qualifications: At least 5 years of security engineering experience with demonstrated independent project ownership; queue-based SOC or triage-only experience is not sufficient. Hands-on PKI engineering experience, including PKI solution design and operations, certificate enrollment protocols such as SCEP and EST, Certificate Policy/Certification Practice Statements (CP/CPS), trusted roles, Levels of Assurance, and NIST SP 800-63. Strong Microsoft Sentinel experience, including KQL/query development, detection rule authoring, dashboard development, and independently led end-to-end security event investigations. Experience owning remediation lifecycle engineering, including remediation-plan review, vulnerability/finding tracking, and validated closure. Nice to Have Skills and Experience: Experience with AI or agentic security tooling, including LLM-assisted code or configuration analysis and prompt engineering for security use cases. Endpoint platform engineering, SSO policy groups, API scripting and automation using Python or PowerShell. Experience with aviation, OT, cyber-physical systems, embedded systems, HSMs, key-management, or code-signing infrastructure. Interview Process: Two interview rounds: the first interview will be virtual, followed by an in-person interview. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $60-$65/Hr on W2 The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global, do not respond or click on any links. Instead, contact us directly at +1 . To report any concerns, please email us at
Oracle to PostgreSQL Migration Consultant Location: Sunnyvale, CA/ Austin, TX (Onsite) FTE/Fulltime Salary : Market- based on exp Rate: Market- based on exp CANDIDATE SHOULD HAVE PYTHON CODING EXPERIENCE AND ORACLE TO POSTGRESQL MIGRATION EXPERIENCE Job Description We are seeking an experienced Data Engineer with proven, hands-on expertise in migrating enterprise database workloads from Oracle to PostgreSQ L. The ideal candidate will lead/support end-to-end migration activities including assessment, schema conversion, data migration, application compatibility, performance tuning, and cutover planning. Key Responsibilities Assess existing Oracle databases (schema, PL/SQL objects, indexes, partitioning, triggers, jobs) to determine migration complexity and approach. Perform schema and object conversion from Oracle to PostgreSQL using tools such as AWS SCT/DMS, Ora2Pg, EDB Migration Toolkit, or custom scripts. Convert PL/SQL procedures, functions, triggers, and packages to PostgreSQL PL/pgSQL, resolving syntax and behavioral differences. Design and execute data migration/validation strategies (full load, incremental/CDC, reconciliation) ensuring zero/minimal data loss. Identify and remediate incompatibilities (data types, sequences, materialized views, partitioning strategies, error handling, connection pooling). Optimize PostgreSQL performance post-migration (indexing strategy, query tuning, vacuum/autovacuum, connection pooling via PgBouncer, partitioning). Collaborate with application teams to update SQL queries, ORM configurations, and connection strings/drivers (JDBC/ODBC/psycopg2). Plan and execute cutover strategy including rollback plans, downtime minimization, and go-live support. Document migration runbooks, technical decisions, and lessons learned. Required Skills & Experience 5+ years of overall database engineering/DBA experience; 3+ years hands-on with Oracle-to-PostgreSQL migration projects (not just theoretical knowledge). Strong command of Oracle (PL/SQL, RMAN, Data Pump, performance tuning) and PostgreSQL (PL/pgSQL, extensions, vacuum internals, replication). Practical experience with migration tools: Ora2Pg, AWS SCT, AWS DMS, EDB Postgres Migration Toolkit, Google DMS, or equivalent. Solid understanding of differences between Oracle and PostgreSQL (sequences, ROWID vs CTID, NVL vs COALESCE, hierarchical queries CONNECT BY vs recursive CTEs, autonomous transactions, packages, etc.). Experience with data validation/reconciliation frameworks to ensure migration accuracy. Familiarity with cloud database services (AWS RDS/Aurora PostgreSQL, Azure, GCP Cloud SQL) is a plus. Scripting skills in Shell, Python for automation of migration tasks. Experience with CI/CD pipelines and version control (Git) for schema/code management. Strong problem-solving skills and ability to work with minimal supervision on complex legacy systems.
08/06/2026
Full time
Oracle to PostgreSQL Migration Consultant Location: Sunnyvale, CA/ Austin, TX (Onsite) FTE/Fulltime Salary : Market- based on exp Rate: Market- based on exp CANDIDATE SHOULD HAVE PYTHON CODING EXPERIENCE AND ORACLE TO POSTGRESQL MIGRATION EXPERIENCE Job Description We are seeking an experienced Data Engineer with proven, hands-on expertise in migrating enterprise database workloads from Oracle to PostgreSQ L. The ideal candidate will lead/support end-to-end migration activities including assessment, schema conversion, data migration, application compatibility, performance tuning, and cutover planning. Key Responsibilities Assess existing Oracle databases (schema, PL/SQL objects, indexes, partitioning, triggers, jobs) to determine migration complexity and approach. Perform schema and object conversion from Oracle to PostgreSQL using tools such as AWS SCT/DMS, Ora2Pg, EDB Migration Toolkit, or custom scripts. Convert PL/SQL procedures, functions, triggers, and packages to PostgreSQL PL/pgSQL, resolving syntax and behavioral differences. Design and execute data migration/validation strategies (full load, incremental/CDC, reconciliation) ensuring zero/minimal data loss. Identify and remediate incompatibilities (data types, sequences, materialized views, partitioning strategies, error handling, connection pooling). Optimize PostgreSQL performance post-migration (indexing strategy, query tuning, vacuum/autovacuum, connection pooling via PgBouncer, partitioning). Collaborate with application teams to update SQL queries, ORM configurations, and connection strings/drivers (JDBC/ODBC/psycopg2). Plan and execute cutover strategy including rollback plans, downtime minimization, and go-live support. Document migration runbooks, technical decisions, and lessons learned. Required Skills & Experience 5+ years of overall database engineering/DBA experience; 3+ years hands-on with Oracle-to-PostgreSQL migration projects (not just theoretical knowledge). Strong command of Oracle (PL/SQL, RMAN, Data Pump, performance tuning) and PostgreSQL (PL/pgSQL, extensions, vacuum internals, replication). Practical experience with migration tools: Ora2Pg, AWS SCT, AWS DMS, EDB Postgres Migration Toolkit, Google DMS, or equivalent. Solid understanding of differences between Oracle and PostgreSQL (sequences, ROWID vs CTID, NVL vs COALESCE, hierarchical queries CONNECT BY vs recursive CTEs, autonomous transactions, packages, etc.). Experience with data validation/reconciliation frameworks to ensure migration accuracy. Familiarity with cloud database services (AWS RDS/Aurora PostgreSQL, Azure, GCP Cloud SQL) is a plus. Scripting skills in Shell, Python for automation of migration tasks. Experience with CI/CD pipelines and version control (Git) for schema/code management. Strong problem-solving skills and ability to work with minimal supervision on complex legacy systems.
Position: Senior Java Engineer - Microservices & Production Support Location: Fort Worth, Texas (Hybrid - onsite Tuesday through Thursday; remote Monday and Friday) Duration: Contract Job ID: 178605 Job Overview: We are seeking a Senior Java Engineer to design, develop, and support large-scale, production-grade microservices. This role requires strong hands-on experience with Java, Spring Boot, Kafka, and production support, along with the ability to deliver high-quality code, meet project timelines, and troubleshoot complex issues. The engineer will work within DevOps-focused squads to build resilient, scalable, and reliable solutions that support enterprise business needs. Responsibilities: Design, develop, test, document, and maintain Java-based microservices and reusable software components. Build and enhance Spring Boot applications and Kafka-based integrations for scalable, event-driven systems. Provide production support, investigate incidents, perform root-cause analysis, and drive corrective actions through resolution. Write clean, reliable, and maintainable code while following organizational development, testing, and documentation standards. Optimize applications and system designs for performance, resiliency, durability, reliability, and scalability. Collaborate with cross-functional engineering teams to support safe, incremental releases and reduce technical debt. Contribute to CI/CD and DevOps practices, including automated testing, source control, and deployment processes. Coach junior engineers on technical craftsmanship, debugging practices, code quality, and engineering best practices. Evaluate emerging technologies and contribute to solution architecture, prototypes, and continuous improvement initiatives. Work within Agile, DevOps-oriented squads of approximately five to six team members. Qualifications: Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline; equivalent experience or training may be considered. 7-9 years of experience designing, developing, and implementing large-scale solutions in production environments. Strong hands-on experience developing microservices using Java and Spring Boot. Hands-on experience with Apache Kafka and event-driven integration patterns. Demonstrated production support experience, including debugging, incident investigation, root-cause analysis, and issue resolution. Strong knowledge of object-oriented design principles, Agile methodologies, and DevOps/CI-CD practices. Ability to deliver quality code, reliably meet project timelines, and communicate technical concepts clearly in writing, verbally, code, and diagrams. Nice to Have Skills and Experience: Experience with PostgreSQL, Redis, Kubernetes, Docker, Git, GitHub Actions, Maven, JUnit, and test automation tools. Experience with REST APIs, GraphQL, cloud platforms such as Azure or AWS, and CI/CD pipelines. Experience with Python, C#, JavaScript/TypeScript, Angular, React, MongoDB, Azure DevOps, Selenium, Postman, SonarQube, Cypress, Cucumber, Playwright, WireMock, or Mockito. Airline industry experience. Interview Process: Two interview rounds: the first interview will be virtual, followed by an onsite hands-on coding interview. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $60 - $65/Hr on W2 The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global, do not respond or click on any links. Instead, contact us directly at +1 . To report any concerns, please email us at
08/06/2026
Full time
Position: Senior Java Engineer - Microservices & Production Support Location: Fort Worth, Texas (Hybrid - onsite Tuesday through Thursday; remote Monday and Friday) Duration: Contract Job ID: 178605 Job Overview: We are seeking a Senior Java Engineer to design, develop, and support large-scale, production-grade microservices. This role requires strong hands-on experience with Java, Spring Boot, Kafka, and production support, along with the ability to deliver high-quality code, meet project timelines, and troubleshoot complex issues. The engineer will work within DevOps-focused squads to build resilient, scalable, and reliable solutions that support enterprise business needs. Responsibilities: Design, develop, test, document, and maintain Java-based microservices and reusable software components. Build and enhance Spring Boot applications and Kafka-based integrations for scalable, event-driven systems. Provide production support, investigate incidents, perform root-cause analysis, and drive corrective actions through resolution. Write clean, reliable, and maintainable code while following organizational development, testing, and documentation standards. Optimize applications and system designs for performance, resiliency, durability, reliability, and scalability. Collaborate with cross-functional engineering teams to support safe, incremental releases and reduce technical debt. Contribute to CI/CD and DevOps practices, including automated testing, source control, and deployment processes. Coach junior engineers on technical craftsmanship, debugging practices, code quality, and engineering best practices. Evaluate emerging technologies and contribute to solution architecture, prototypes, and continuous improvement initiatives. Work within Agile, DevOps-oriented squads of approximately five to six team members. Qualifications: Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline; equivalent experience or training may be considered. 7-9 years of experience designing, developing, and implementing large-scale solutions in production environments. Strong hands-on experience developing microservices using Java and Spring Boot. Hands-on experience with Apache Kafka and event-driven integration patterns. Demonstrated production support experience, including debugging, incident investigation, root-cause analysis, and issue resolution. Strong knowledge of object-oriented design principles, Agile methodologies, and DevOps/CI-CD practices. Ability to deliver quality code, reliably meet project timelines, and communicate technical concepts clearly in writing, verbally, code, and diagrams. Nice to Have Skills and Experience: Experience with PostgreSQL, Redis, Kubernetes, Docker, Git, GitHub Actions, Maven, JUnit, and test automation tools. Experience with REST APIs, GraphQL, cloud platforms such as Azure or AWS, and CI/CD pipelines. Experience with Python, C#, JavaScript/TypeScript, Angular, React, MongoDB, Azure DevOps, Selenium, Postman, SonarQube, Cypress, Cucumber, Playwright, WireMock, or Mockito. Airline industry experience. Interview Process: Two interview rounds: the first interview will be virtual, followed by an onsite hands-on coding interview. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $60 - $65/Hr on W2 The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global, do not respond or click on any links. Instead, contact us directly at +1 . To report any concerns, please email us at
Position: Senior Security Engineer - PKI & Detection, Aircraft Security Location: Fort Worth Texas (Hybrid - onsite Tuesday through Thursday; remote Monday and Friday) Duration: Contract Job ID: 178660 Job Overview: We are seeking a Senior Security Engineer to support aircraft security initiatives focused on detection, remediation, and Public Key Infrastructure (PKI). This role will independently design and operate security solutions, investigate security events, develop detections, and drive remediation activities through validated closure. The ideal candidate brings strong hands-on PKI engineering expertise, Microsoft Sentinel detection engineering experience, and the ability to work across technical teams to improve security, reliability, and scalability. Responsibilities: Design, build, test, document, and maintain security engineering solutions, scripts, processes, and reusable components in accordance with organizational standards. Develop and tune Microsoft Sentinel detections, KQL queries, analytics rules, dashboards, and investigation workflows. Conduct end-to-end security event investigations, perform root-cause analysis, and produce clear written documentation of findings and corrective actions. Own remediation lifecycle activities, including remediation-plan reviews, vulnerability and finding tracking, and validation of closure. Design and operate PKI solutions, including certificate enrollment, authentication, software signing, validation, and supporting key-management processes. Partner with security and engineering teams to incorporate security-conscious practices early in the system development lifecycle. Identify technical risks related to scalability, latency, durability, and security, and lead practical mitigation strategies. Guide junior engineers on technical craftsmanship and contribute to continuous improvement of engineering practices. Explore emerging technologies and develop prototypes that may be incorporated into security architecture and operational solutions. Qualifications: At least 5 years of security engineering experience with demonstrated independent project ownership; queue-based SOC or triage-only experience is not sufficient. Hands-on PKI engineering experience, including PKI solution design and operations, certificate enrollment protocols such as SCEP and EST, Certificate Policy/Certification Practice Statements (CP/CPS), trusted roles, Levels of Assurance, and NIST SP 800-63. Strong Microsoft Sentinel experience, including KQL/query development, detection rule authoring, dashboard development, and independently led end-to-end security event investigations. Experience owning remediation lifecycle engineering, including remediation-plan review, vulnerability/finding tracking, and validated closure. Nice to Have Skills and Experience: Experience with AI or agentic security tooling, including LLM-assisted code or configuration analysis and prompt engineering for security use cases. Endpoint platform engineering, SSO policy groups, API scripting and automation using Python or PowerShell. Experience with aviation, OT, cyber-physical systems, embedded systems, HSMs, key-management, or code-signing infrastructure. Interview Process: Two interview rounds: the first interview will be virtual, followed by an in-person interview. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $60-$65/Hr on W2 The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global, do not respond or click on any links. Instead, contact us directly at +1 . To report any concerns, please email us at
08/06/2026
Full time
Position: Senior Security Engineer - PKI & Detection, Aircraft Security Location: Fort Worth Texas (Hybrid - onsite Tuesday through Thursday; remote Monday and Friday) Duration: Contract Job ID: 178660 Job Overview: We are seeking a Senior Security Engineer to support aircraft security initiatives focused on detection, remediation, and Public Key Infrastructure (PKI). This role will independently design and operate security solutions, investigate security events, develop detections, and drive remediation activities through validated closure. The ideal candidate brings strong hands-on PKI engineering expertise, Microsoft Sentinel detection engineering experience, and the ability to work across technical teams to improve security, reliability, and scalability. Responsibilities: Design, build, test, document, and maintain security engineering solutions, scripts, processes, and reusable components in accordance with organizational standards. Develop and tune Microsoft Sentinel detections, KQL queries, analytics rules, dashboards, and investigation workflows. Conduct end-to-end security event investigations, perform root-cause analysis, and produce clear written documentation of findings and corrective actions. Own remediation lifecycle activities, including remediation-plan reviews, vulnerability and finding tracking, and validation of closure. Design and operate PKI solutions, including certificate enrollment, authentication, software signing, validation, and supporting key-management processes. Partner with security and engineering teams to incorporate security-conscious practices early in the system development lifecycle. Identify technical risks related to scalability, latency, durability, and security, and lead practical mitigation strategies. Guide junior engineers on technical craftsmanship and contribute to continuous improvement of engineering practices. Explore emerging technologies and develop prototypes that may be incorporated into security architecture and operational solutions. Qualifications: At least 5 years of security engineering experience with demonstrated independent project ownership; queue-based SOC or triage-only experience is not sufficient. Hands-on PKI engineering experience, including PKI solution design and operations, certificate enrollment protocols such as SCEP and EST, Certificate Policy/Certification Practice Statements (CP/CPS), trusted roles, Levels of Assurance, and NIST SP 800-63. Strong Microsoft Sentinel experience, including KQL/query development, detection rule authoring, dashboard development, and independently led end-to-end security event investigations. Experience owning remediation lifecycle engineering, including remediation-plan review, vulnerability/finding tracking, and validated closure. Nice to Have Skills and Experience: Experience with AI or agentic security tooling, including LLM-assisted code or configuration analysis and prompt engineering for security use cases. Endpoint platform engineering, SSO policy groups, API scripting and automation using Python or PowerShell. Experience with aviation, OT, cyber-physical systems, embedded systems, HSMs, key-management, or code-signing infrastructure. Interview Process: Two interview rounds: the first interview will be virtual, followed by an in-person interview. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $60-$65/Hr on W2 The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global, do not respond or click on any links. Instead, contact us directly at +1 . To report any concerns, please email us at
Ready to take on meaningful challenges and shape the next generation of mobility? Joining OPmobility means stepping into a global group with a purpose to keep people and goods moving safely, smarter, and sustainably everywhere. Title: Plant Automation Engineer Work Location: Anderson, SC Activities Dedication to safety Closely monitor quality levels and root causes; correct any maintenance related non-conformances Develop, Implement, and evaluate continuous improvement plans Coordinate all technical activity and maintain accurate records pertaining to the system PLC equipment Support and train the maintenance staff appropriately to ensure all system automation, PLC's and robots are maintained to the optimum operating level Participate fully in the OPmobility continuous improvement team activities as directed by the Maintenance manager to ensure CI goals are met Coordinate modifications and new projects automation, PLC and robotic equipment as required ensuring all work is in accordance with the local and state regulations Develop robust logic for optimum operational uptime and repeatability Continuously review and consider new technologies (PLC or otherwise) as they apply to OPmobility. Make recommendations to maintenance team as to their benefits along with feasibility and justification for such technologies Provide automation support as required as it applies to all other aspects of the current and any future systems. Provide regular progress reports on the timeline schedules for all projects Coordinate all training activity for the appropriate personnel regarding the design intent, operation, maintenance and programming of system automation, PLC equipment, robotic equipment and associates interfaces Assume a leadership role and provide support to the maintenance technicians and staff in the operation and maintenance of all system robotic equipment to the extent that all system uptime goals are met. Closely monitor equipment availability levels, perform root cause analysis, and resolve issues Create and drive actions to cross functional team members Perform other duties as directed Key Technical Competencies Field bus: Controlnet, Modbus, Profibus Integration to injection machines Must have strong PLC skills Automotive assembly, injection, and paint a plus Must have demonstrated project and continuous improvement experience Must have sound knowledge and understanding of the electrical code. Qualifications Engineering degree required (industrial preferred) Good capacity in spoken and written English Good knowledge of manufacturing processes, capital equipment installation, and integration into the plant Communication capability skills towards all management levels Safety minded Team player, self-determined in approach to tasks, systematic and disciplined approach to activities Previous Experience Experience with project launches (involving equipment commissioning and trouble shooting in industrial environment) Maintenance experience in industrial environment Experience in digitalization and transformation to 4.0 industry. At OPmobility, people truly matter. We are committed to building inclusive teams, promoting diversity and equality, and ensuring that every application is considered fairly - because the future of mobility is built by diverse perspectives, bold ideas, and people who dare to move forward. Innovation is therefore not a buzzword, but a natural part of everyday work. You'll grow in an international environment where cutting-edge technologies, industrial excellence, and real-world impact come together to tackle the challenges of tomorrow's automotive industry. Founded in 1946 by Pierre Burelle, OPmobility, known until 2024 as Plastic Omnium, has transformed itself into a player in sustainable and connected mobility. Today, OPmobility develops technological solutions across four areas of expertise: exterior and lighting systems, the integration of complex modules, technologies related to energy storage, hydrogen and electrification, and a division dedicated to the development of embedded software and digital solutions. With €11.5 billion in revenue in 2025, 152 factories, 40 R&D centers, and nearly 38,100 employees across 28 countries, OPmobility combines global scale with local impact. All driven by a shared ambition to accelerate the automotive energy transition.
08/06/2026
Full time
Ready to take on meaningful challenges and shape the next generation of mobility? Joining OPmobility means stepping into a global group with a purpose to keep people and goods moving safely, smarter, and sustainably everywhere. Title: Plant Automation Engineer Work Location: Anderson, SC Activities Dedication to safety Closely monitor quality levels and root causes; correct any maintenance related non-conformances Develop, Implement, and evaluate continuous improvement plans Coordinate all technical activity and maintain accurate records pertaining to the system PLC equipment Support and train the maintenance staff appropriately to ensure all system automation, PLC's and robots are maintained to the optimum operating level Participate fully in the OPmobility continuous improvement team activities as directed by the Maintenance manager to ensure CI goals are met Coordinate modifications and new projects automation, PLC and robotic equipment as required ensuring all work is in accordance with the local and state regulations Develop robust logic for optimum operational uptime and repeatability Continuously review and consider new technologies (PLC or otherwise) as they apply to OPmobility. Make recommendations to maintenance team as to their benefits along with feasibility and justification for such technologies Provide automation support as required as it applies to all other aspects of the current and any future systems. Provide regular progress reports on the timeline schedules for all projects Coordinate all training activity for the appropriate personnel regarding the design intent, operation, maintenance and programming of system automation, PLC equipment, robotic equipment and associates interfaces Assume a leadership role and provide support to the maintenance technicians and staff in the operation and maintenance of all system robotic equipment to the extent that all system uptime goals are met. Closely monitor equipment availability levels, perform root cause analysis, and resolve issues Create and drive actions to cross functional team members Perform other duties as directed Key Technical Competencies Field bus: Controlnet, Modbus, Profibus Integration to injection machines Must have strong PLC skills Automotive assembly, injection, and paint a plus Must have demonstrated project and continuous improvement experience Must have sound knowledge and understanding of the electrical code. Qualifications Engineering degree required (industrial preferred) Good capacity in spoken and written English Good knowledge of manufacturing processes, capital equipment installation, and integration into the plant Communication capability skills towards all management levels Safety minded Team player, self-determined in approach to tasks, systematic and disciplined approach to activities Previous Experience Experience with project launches (involving equipment commissioning and trouble shooting in industrial environment) Maintenance experience in industrial environment Experience in digitalization and transformation to 4.0 industry. At OPmobility, people truly matter. We are committed to building inclusive teams, promoting diversity and equality, and ensuring that every application is considered fairly - because the future of mobility is built by diverse perspectives, bold ideas, and people who dare to move forward. Innovation is therefore not a buzzword, but a natural part of everyday work. You'll grow in an international environment where cutting-edge technologies, industrial excellence, and real-world impact come together to tackle the challenges of tomorrow's automotive industry. Founded in 1946 by Pierre Burelle, OPmobility, known until 2024 as Plastic Omnium, has transformed itself into a player in sustainable and connected mobility. Today, OPmobility develops technological solutions across four areas of expertise: exterior and lighting systems, the integration of complex modules, technologies related to energy storage, hydrogen and electrification, and a division dedicated to the development of embedded software and digital solutions. With €11.5 billion in revenue in 2025, 152 factories, 40 R&D centers, and nearly 38,100 employees across 28 countries, OPmobility combines global scale with local impact. All driven by a shared ambition to accelerate the automotive energy transition.
Software Development Engineer-Satellite Storage Health Location: Redmond, WA (Onsite) - first preference will be for local profiles. FTE/Fulltime Salary: Market- Based on candidate exp. PROFILES LESS THAN 10 YEARS OF EXPERIENCE preferred Job Summary: Amazon Leo is seeking a highly skilled Software Development Engineer to join our satellite software platforms team. You will be responsible for the development, maintenance, and operational support of embedded software systems powering over-the-air (OTA) updates and storage management across our low-earth-orbit satellite infrastructure. Key Responsibilities: - Design, develop, test, and deploy embedded software components supporting the OTA Agent platform - Investigate, triage, and resolve complex production software issues across embedded, storage, and platform services; perform root cause analysis and implement corrective actions - Develop new features, enhancements, and bug fixes using Java, Python, and shell scripting within a Linux-based development environment - Collaborate with cross-functional engineering and operational teams through Agile ceremonies including sprint planning, backlog refinement, standups, and retrospectives - Provide technical recommendations supporting platform scalability, reliability, and operational improvements - Contribute to engineering documentation, knowledge transfer materials, and code reviews in accordance with Amazon development standards - Develop and maintain automated testing capabilities supporting SW Provisioning and OTA Agent software releases; drive continuous improvement in test automation coverage. Required Skills: - 7+ years of professional software development experience in industry - Strong proficiency in Java and Python - Solid experience with shell scripting (Bash/sh) - Hands-on working experience with Linux-based development environments (development, debugging, deployment) - Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field (or equivalent practical experience) - Experience with software testing methodologies and test automation frameworks - Strong problem-solving skills with the ability to investigate and resolve complex production issues - Experience working in Agile/Scrum development environments Preferred Qualifications: - Experience in embedded systems development - Familiarity with C++ and/or Rust programming languages - Experience with over-the-air (OTA) update systems or software deployment pipelines - Background in satellite systems, aerospace, or IoT device platforms - Experience with on-call operations, incident management, and root cause analysis - Knowledge of storage management systems and distributed software deployment - Experience working with mission-critical or safety-critical software systems - Familiarity with CI/CD pipelines and build automation tools
08/06/2026
Full time
Software Development Engineer-Satellite Storage Health Location: Redmond, WA (Onsite) - first preference will be for local profiles. FTE/Fulltime Salary: Market- Based on candidate exp. PROFILES LESS THAN 10 YEARS OF EXPERIENCE preferred Job Summary: Amazon Leo is seeking a highly skilled Software Development Engineer to join our satellite software platforms team. You will be responsible for the development, maintenance, and operational support of embedded software systems powering over-the-air (OTA) updates and storage management across our low-earth-orbit satellite infrastructure. Key Responsibilities: - Design, develop, test, and deploy embedded software components supporting the OTA Agent platform - Investigate, triage, and resolve complex production software issues across embedded, storage, and platform services; perform root cause analysis and implement corrective actions - Develop new features, enhancements, and bug fixes using Java, Python, and shell scripting within a Linux-based development environment - Collaborate with cross-functional engineering and operational teams through Agile ceremonies including sprint planning, backlog refinement, standups, and retrospectives - Provide technical recommendations supporting platform scalability, reliability, and operational improvements - Contribute to engineering documentation, knowledge transfer materials, and code reviews in accordance with Amazon development standards - Develop and maintain automated testing capabilities supporting SW Provisioning and OTA Agent software releases; drive continuous improvement in test automation coverage. Required Skills: - 7+ years of professional software development experience in industry - Strong proficiency in Java and Python - Solid experience with shell scripting (Bash/sh) - Hands-on working experience with Linux-based development environments (development, debugging, deployment) - Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field (or equivalent practical experience) - Experience with software testing methodologies and test automation frameworks - Strong problem-solving skills with the ability to investigate and resolve complex production issues - Experience working in Agile/Scrum development environments Preferred Qualifications: - Experience in embedded systems development - Familiarity with C++ and/or Rust programming languages - Experience with over-the-air (OTA) update systems or software deployment pipelines - Background in satellite systems, aerospace, or IoT device platforms - Experience with on-call operations, incident management, and root cause analysis - Knowledge of storage management systems and distributed software deployment - Experience working with mission-critical or safety-critical software systems - Familiarity with CI/CD pipelines and build automation tools
Date Posted: 2026-06-24 Country: United States of America Location: US-CO-AURORA-S E Centretech Pkwy BLDG S75 Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: TS/SCI with Polygraph Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedom and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. At Raytheon, the foundation of everything we do is rooted in our values and a higher calling - to help our nation and allies defend freedoms and deter aggression. We bring the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. Our team solves tough, meaningful problems that create a safer, more secure world. We have an exciting opportunity for a Senior. Principal Platform DevSecOps Engineer, supporting one of our premier programs in the business unit where you will be working with a cross-disciplinary team of Platform engineers and Systems Administrators leading the industry in ground systems solutions. This role entails leading the design, development, implementation, integration, and sustainment of a cloud-based compute, network, and storage infrastructure. The position also focuses on platform modernization by incorporating emerging technologies to optimize performance and efficiency. Utilizing DevOps/DevSecOps methodologies, tools, and automation, the role is critical in streamlining processes, enhancing collaboration, and accelerating software release cycles. As part of the team, you will contribute to the development and operational environments of a large-scale program that supports a critical national asset, ensuring its reliability and innovation in line with mission objectives. Note This position will be filled onsite at the RTX Facility in Aurora CO. What You Will Do Platform Development and Optimization: You will Contribute to the architecture, design, integration, and support of platform and infrastructure environments across build, integration & test, and production stages. Focus on ensuring these environments are optimized for performance, reliability, and scalability within cloud-based ecosystems Best Practices and Automation: You will Utilize industry and company best practices to enhance scalability, consistency, and infrastructure efficiency, while reducing deployment time and automating configuration management processes Cross-Team Collaboration: You will Work closely with software engineers, data scientists, and other agile development teams to design and implement resilient and scalable platform solutions Security and Compliance Integration: You will Embed security and compliance measures into the platform, including services like encryption and access management Operational Support: you will Provide ongoing operational support to maintain the stability, functionality, and performance of the platform Qualifications You Must Have Typically requires BS/BA Degree in Science, Technology Engineering Math (STEM) in Computer Science, Computer Engineering, Information Technology or Physics and a minimum 10 years of related work experience Experience in the installation, configuration, and maintenance of RedHat Linux operating systems Experience with automation frameworks such as Terraform, Ansible, and Chef to streamline infrastructure deployment and management Experience programming or scripting languages such as Python and Bash for automation, configuration, and system operations Active and Current TS/SCI with CI Poly security clearance is required on day 1. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Qualifications We Prefer Experience designing, implementing, and integrating cloud-based systems on infrastructure platforms like AWS Experience in analyzing performance and troubleshooting applications and infrastructure services on Linux-based operating systems Strong infrastructure background managing and troubleshooting servers, networks, storage, and virtualization technologies DevSecOps Framework: Proficiency in developing, testing, and delivering applications within a DevSecOps framework Experience with cloud platforms, preferably AWS, including designing, deploying, and securing cloud services AWS Services Proficiency: Hands-on experience with AWS services such as EC2, EKS, S3, CloudWatch, IAM, and VPC, with a focus on secure and scalable deployments Proficiency in designing, implementing, and integrating platform infrastructure services using containerization technologies such as Kubernetes, Docker, and/or Podman Hands-on experience in deploying, configuring, and supporting CI/CD pipeline tools such as Jira, Confluence, Jenkins, Artifactory, GitLab and Helm Familiarity with security scanning tools like Nessus COTS/FOSS Products: Experience in installation, configuration, and integration of Commercial Off-The-Shelf (COTS) and Free and Open-Source Software (FOSS) products DoD 8570 IAT Level II Certification: Must meet Department of Defense 8570 Information Assurance Technical (IAT) Level II requirements, such as holding a Security+ CE or equivalent certification. What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Safety, Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligibility Learn More & Apply Now! Please consider the following role type definition as you apply for this role Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products This position requires security clearance. DCSA Consolidated Adjudication Services (DCSA CAS), an agency of the Department of Defense, handles and adjudicates the security clearance process. More information about Security Clearances can be found on the US Department of State government website here: Location: Aurora, CO: We are RTX As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 132,400 USD - 251,600 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class . click apply for full job details
08/06/2026
Full time
Date Posted: 2026-06-24 Country: United States of America Location: US-CO-AURORA-S E Centretech Pkwy BLDG S75 Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: TS/SCI with Polygraph Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedom and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. At Raytheon, the foundation of everything we do is rooted in our values and a higher calling - to help our nation and allies defend freedoms and deter aggression. We bring the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. Our team solves tough, meaningful problems that create a safer, more secure world. We have an exciting opportunity for a Senior. Principal Platform DevSecOps Engineer, supporting one of our premier programs in the business unit where you will be working with a cross-disciplinary team of Platform engineers and Systems Administrators leading the industry in ground systems solutions. This role entails leading the design, development, implementation, integration, and sustainment of a cloud-based compute, network, and storage infrastructure. The position also focuses on platform modernization by incorporating emerging technologies to optimize performance and efficiency. Utilizing DevOps/DevSecOps methodologies, tools, and automation, the role is critical in streamlining processes, enhancing collaboration, and accelerating software release cycles. As part of the team, you will contribute to the development and operational environments of a large-scale program that supports a critical national asset, ensuring its reliability and innovation in line with mission objectives. Note This position will be filled onsite at the RTX Facility in Aurora CO. What You Will Do Platform Development and Optimization: You will Contribute to the architecture, design, integration, and support of platform and infrastructure environments across build, integration & test, and production stages. Focus on ensuring these environments are optimized for performance, reliability, and scalability within cloud-based ecosystems Best Practices and Automation: You will Utilize industry and company best practices to enhance scalability, consistency, and infrastructure efficiency, while reducing deployment time and automating configuration management processes Cross-Team Collaboration: You will Work closely with software engineers, data scientists, and other agile development teams to design and implement resilient and scalable platform solutions Security and Compliance Integration: You will Embed security and compliance measures into the platform, including services like encryption and access management Operational Support: you will Provide ongoing operational support to maintain the stability, functionality, and performance of the platform Qualifications You Must Have Typically requires BS/BA Degree in Science, Technology Engineering Math (STEM) in Computer Science, Computer Engineering, Information Technology or Physics and a minimum 10 years of related work experience Experience in the installation, configuration, and maintenance of RedHat Linux operating systems Experience with automation frameworks such as Terraform, Ansible, and Chef to streamline infrastructure deployment and management Experience programming or scripting languages such as Python and Bash for automation, configuration, and system operations Active and Current TS/SCI with CI Poly security clearance is required on day 1. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Qualifications We Prefer Experience designing, implementing, and integrating cloud-based systems on infrastructure platforms like AWS Experience in analyzing performance and troubleshooting applications and infrastructure services on Linux-based operating systems Strong infrastructure background managing and troubleshooting servers, networks, storage, and virtualization technologies DevSecOps Framework: Proficiency in developing, testing, and delivering applications within a DevSecOps framework Experience with cloud platforms, preferably AWS, including designing, deploying, and securing cloud services AWS Services Proficiency: Hands-on experience with AWS services such as EC2, EKS, S3, CloudWatch, IAM, and VPC, with a focus on secure and scalable deployments Proficiency in designing, implementing, and integrating platform infrastructure services using containerization technologies such as Kubernetes, Docker, and/or Podman Hands-on experience in deploying, configuring, and supporting CI/CD pipeline tools such as Jira, Confluence, Jenkins, Artifactory, GitLab and Helm Familiarity with security scanning tools like Nessus COTS/FOSS Products: Experience in installation, configuration, and integration of Commercial Off-The-Shelf (COTS) and Free and Open-Source Software (FOSS) products DoD 8570 IAT Level II Certification: Must meet Department of Defense 8570 Information Assurance Technical (IAT) Level II requirements, such as holding a Security+ CE or equivalent certification. What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value: Safety, Trust, Respect, Accountability, Collaboration, and Innovation Relocation Eligibility Learn More & Apply Now! Please consider the following role type definition as you apply for this role Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products This position requires security clearance. DCSA Consolidated Adjudication Services (DCSA CAS), an agency of the Department of Defense, handles and adjudicates the security clearance process. More information about Security Clearances can be found on the US Department of State government website here: Location: Aurora, CO: We are RTX As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 132,400 USD - 251,600 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class . click apply for full job details
Lead Machine Learning Engineer (Manager IC) As a Capital One Machine Learning Engineer (MLE), you'll join an Agile team building and productionizing foundation models at scale. Our work centers on self-supervised learning for transformer architectures - pretraining on Capital One's rich, large-scale behavioral data to learn representations that power applications across use cases such as fraud, marketing, and servicing . You'll participate in the detailed technical design, development, and implementation of these systems, spanning model architecture, large-scale training and representation learning, and the engineering required to serve models reliably in production. You'll develop and review model and application code, drive machine learning architectural decisions, and ensure the high availability and performance of our applications. And you'll have the opportunity to continuously learn and apply the latest innovations in self-supervised learning, transformer modeling, and ML engineering best practices. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer San Jose, CA: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
08/06/2026
Full time
Lead Machine Learning Engineer (Manager IC) As a Capital One Machine Learning Engineer (MLE), you'll join an Agile team building and productionizing foundation models at scale. Our work centers on self-supervised learning for transformer architectures - pretraining on Capital One's rich, large-scale behavioral data to learn representations that power applications across use cases such as fraud, marketing, and servicing . You'll participate in the detailed technical design, development, and implementation of these systems, spanning model architecture, large-scale training and representation learning, and the engineering required to serve models reliably in production. You'll develop and review model and application code, drive machine learning architectural decisions, and ensure the high availability and performance of our applications. And you'll have the opportunity to continuously learn and apply the latest innovations in self-supervised learning, transformer modeling, and ML engineering best practices. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer San Jose, CA: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer San Jose, CA: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
08/06/2026
Full time
Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer San Jose, CA: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer San Jose, CA: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
08/06/2026
Full time
Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer San Jose, CA: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead Machine Learning Engineer (Enterprise Platforms Technology) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
08/06/2026
Full time
Lead Machine Learning Engineer (Enterprise Platforms Technology) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine exceptional products for our customers. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers. Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI. Fine-tune, develop and evaluate machine learning and foundation models, Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One. Leverage a broad stack of Open Source and SaaS AI technologies. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues. Retrain, maintain, and monitor models in production. Construct optimized data pipelines to feed ML models. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. You are a passionate communicator, comfortable with explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production Strategic & Business-Oriented: You think beyond the technology, deeply understanding business needs and how AI can solve them. You don't just build; you strategize and prioritize work that delivers the greatest business value. Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team. Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem-solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions. Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities. A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 7+ years of experience designing, developing, delivering, and supporting AI services at scale 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation (RAG) 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace . click apply for full job details
08/06/2026
Full time
Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine exceptional products for our customers. In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities. In this role at Risk Tech, you will work with our GRC team and partners across the company to build and deploy proprietary solutions for Risk management that are powered by state-of-the-art AI technology. Our products, enhanced with the transformative power of AI, are central to our business and deliver tremendous customer value. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers. Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI. Fine-tune, develop and evaluate machine learning and foundation models, Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One. Leverage a broad stack of Open Source and SaaS AI technologies. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues. Retrain, maintain, and monitor models in production. Construct optimized data pipelines to feed ML models. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. You are a passionate communicator, comfortable with explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Passion for staying abreast of the latest AI research and AI systems, and judiciously applying novel techniques in production Strategic & Business-Oriented: You think beyond the technology, deeply understanding business needs and how AI can solve them. You don't just build; you strategize and prioritize work that delivers the greatest business value. Highly Collaborative & Transparent: You are a natural partner, working seamlessly across engineering, product, and data science teams. You communicate your progress, blockers, and decisions clearly and proactively, ensuring everyone is aligned. You love sharing knowledge and insights and are committed to the success of the entire team. Technically Mature & Humble: You possess a strong foundation in engineering and mathematics. You are a resilient problem-solver who can bring clarity to complex, undefined problems and articulate your findings concisely. You demonstrate professional maturity by committing to and executing on team decisions. Flexible & Fungible: You are eager to roll up your sleeves and contribute wherever the team needs you most. You are comfortable working across different aspects of the tech stack and adapting to evolving priorities. A Lifelong Learner: You love staying current with the latest AI research and can apply novel techniques to production systems judiciously, always with a focus on business impact. Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 7+ years of experience designing, developing, delivering, and supporting AI services at scale 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing AI and ML algorithms or technologies using Python 2+ years of experience with Retrieval Augmented Generation (RAG) 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Richmond, VA: $179,400 - $204,700 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace . click apply for full job details
Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
08/06/2026
Full time
Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 2 years of experience building, scaling, and optimizing ML systems Preferred Qualifications: Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Richmond, VA: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
08/06/2026
Full time
Senior Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Richmond, VA: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
