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Capital One Logo Capital One · IT - Software Development

Lead Machine Learning Engineer

United States, San Francisco, California Employment contract 197300.00 - 245600.00 USD / Year · Job Posted April 24, 2026
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Job Description

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.

Job Responsibility

  • Design, build, and/or deliver ML models and components that solve real-world business problems
  • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues
  • 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
  • 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 or Golang

Requirements

  • Bachelor's Degree
  • At least 6 years of experience designing and building data-intensive solutions using distributed computing
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 2 years of experience building, scaling, and optimizing ML systems

Nice to have

  • 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

What we offer

  • Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
  • Health, financial and other benefits
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Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile tea...
Location
Location
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Salary:
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capitalone.com Logo
Capital One
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 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
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  • 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
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  • Use programming languages like Golang, Python, Scala, or Java
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  • performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
  • comprehensive, competitive, and inclusive set of health, financial and other benefits
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As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile tea...
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Expiration Date
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  • At least 4 years of experience programming with Python, Scala, or Java
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  • 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
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  • 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
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  • At least 4 years of experience programming with Python, Scala, or Java
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  • 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
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  • Fulltime
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Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile tea...
Location
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United States , McLean
Salary
Salary:
197300.00 - 225100.00 USD / Year
capitalone.com Logo
Capital One
Expiration Date
Until further notice
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Requirements
Requirements
  • Bachelor’s Degree
  • At least 6 years of experience designing and building data-intensive solutions using distributed computing
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 2 years of experience building, scaling, and optimizing ML systems
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  • Inform ML infrastructure decisions using understanding of ML modeling techniques
  • 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
  • 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
  • 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
What we offer
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  • Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
  • Comprehensive, competitive, and inclusive set of health, financial and other benefits that support total well-being
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Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile tea...
Location
Location
United States , McLean
Salary
Salary:
197300.00 - 225100.00 USD / Year
capitalone.com Logo
Capital One
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor’s Degree
  • At least 6 years of experience designing and building data-intensive solutions using distributed computing
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 2 years of experience building, scaling, and optimizing ML systems
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  • Design, build, and/or deliver ML models and components that solve real-world business problems
  • Inform ML infrastructure decisions using understanding of ML modeling techniques
  • 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
  • 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
  • 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
What we offer
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  • performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
  • comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
  • Fulltime
Read More
Arrow Right

Lead Machine Learning Engineer

At Capital One, we are creating responsible and reliable AI systems, changing ba...
Location
Location
United States , San Francisco; New York; San Jose; Cambridge; McLean
Salary
Salary:
197300.00 - 245600.00 USD / Year
capitalone.com Logo
Capital One
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor’s Degree
  • At least 6 years of experience designing and building data-intensive solutions using distributed computing
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 2 years of experience building, scaling, and optimizing ML systems
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  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with a cross-functional team of engineers, research scientists, technical program managers, and product managers.
  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
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  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
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  • 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.
What we offer
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  • performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
  • comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
  • Fulltime
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Arrow Right

Lead Machine Learning Engineer

At Capital One, we are creating responsible and reliable AI systems, changing ba...
Location
Location
United States , New York; San Francisco; San Jose; Cambridge; McLean
Salary
Salary:
197300.00 - 245600.00 USD / Year
capitalone.com Logo
Capital One
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor’s Degree
  • At least 6 years of experience designing and building data-intensive solutions using distributed computing
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 2 years of experience building, scaling, and optimizing ML systems
Job Responsibility
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  • Design, build, and/or deliver ML models and components that solve real-world business problems
  • 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
  • Design, develop, test, deploy, and support AI software components including large language model inference, similarity search, model evaluation, experimentation, governance, and observability
  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance of large scale production AI systems
  • Contribute to the technical vision and the long term roadmap of foundational AI systems
  • 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
What we offer
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  • Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
  • Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
  • Fulltime
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