Sr. Lead Machine Learning Engineer (IC)

Capital One; Richmond (VA); On-site; USD 209,000 - 238,500; Full time

Job summary

Capital One in Richmond, VA is seeking a Sr. Lead Machine Learning Engineer (IC) to design, build, and productionize data‑intensive ML solutions at scale.

You will own ML architecture, collaborate with Product and Data Science, optimize models, build data pipelines, and drive CI/CD, monitoring, and governance for reliable, responsible AI.

The role requires strong leadership, deep distributed computing experience, and hands‑on coding in Python/Scala/Java.

Qualifications

• Bachelor's degree required; advanced degree preferred.
• 8+ years designing data-intensive solutions with distributed computing.
• 4+ years programming in Python, Scala, or Java.
• 3+ years building and scaling ML systems.
• 2+ years leading teams developing ML solutions.

Responsibilities

• Design, build, and deliver ML models and components with Product/Data Science teams.
• Inform infrastructure choices including data, features, and model selection.
• Write, test, and deploy production ML code; automate tests and deployment.
• Collaborate in an Agile team to enable big data and ML applications.
• Retrain, monitor, and maintain models in production.
• Leverage cloud-based architectures to deliver scalable ML models.
• Construct data pipelines to feed ML models.
• Implement CI/CD, monitoring, and governance for responsible AI.

Skills

Distributed computing

Python/Scala/Java

ML systems

Team leadership

Cloud platforms (AWS/Azure/GCP)

ML frameworks (scikit-learn, PyTorch,

Education

Bachelor's Degree

Master's or Doctoral Degree

Tools

Scikit-learn

PyTorch

Dask

Spark

XGBoost

Job description

Sr. 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 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 XGboost
• 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
• Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion

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

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 (https://www.capitalonecareers.com/benefits). Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.

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 4901-4920; 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.