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Lead Machine Learning Engineer

Capital One McLean, VA

McLean, VA

Today

$197k - $225k/yr Full time Manager Artificial Intelligence AWS

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Job Description

Capital One is hiring a Lead Machine Learning Engineer (Manager IC) to join an Agile team focused on building and productionizing foundation models. The work centers on self-supervised learning for transformer architectures, with an emphasis on creating ML systems and data pipelines that can perform reliably once deployed.

This onsite role is based in McLean, VA and supports a production-oriented approach to machine learning, including model retraining, monitoring, governance, and scalable infrastructure across cloud platforms.

What you’ll do

Contribute to technical design, development, and implementation across model architecture, large-scale training, and representation learning, plus the engineering needed for dependable production serving.
Develop and review model and application code, influence machine learning architectural decisions, and help ensure high availability and performance of applications.
Design, build, and/or deliver ML models and components that address real business needs in collaboration with Product and Data Science teams.
Apply ML modeling expertise to guide infrastructure decisions, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality considerations, bias/variance tradeoffs, and validation.
Address complex problems through application code development and testing, ML model development and validation, and automation of tests and deployments.
Work within a cross-functional Agile team to create and improve software enabling state-of-the-art big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
Build optimized data pipelines that supply inputs to ML models.
Use continuous integration and continuous deployment practices, including test automation and monitoring, to support successful deployment of model and application code.
Maintain well-managed code to reduce vulnerabilities, ensure models are governed from a risk perspective, and follow best practices in Responsible and Explainable AI.
Use programming languages such as Python, Scala, or Java to implement solutions.

Required qualifications

Bachelor’s Degree
6+ years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply).
4+ years of experience programming with Python, Scala, or Java.
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 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 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+ year 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, using capabilities beyond basic code completion.

Tools and technologies

Python, Scala, Java, scikit-learn, PyTorch, Dask, Spark, TensorFlow
AWS, Azure, Google Cloud Platform

Compensation: USD 197,300 - 225,100 per year (full-time). Performance-based incentive compensation may be available, which may include cash bonus(es) and/or long-term incentives (LTI).

Additional notes: Capital One does not sponsor a new applicant for employment authorization or offer immigration related support for this position. No agencies please. Capital One is an equal opportunity employer and promotes a drug-free workplace.

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