Sr. Lead Machine Learning Engineer

Capital One; McLean (VA); On-site; USD 229,900 - 262,400; Full time

Benefits offered by this job

Health Benefits

Performance-based Incentives

Inclusive Work Environment

Job summary

Capital One is seeking a Machine Learning Engineer (MLE) in McLean, VA to help scale machine learning applications. You will design and develop ML models, collaborate with teams, and ensure performance while maintaining high standards in code quality and model governance.

The ideal candidate will have significant experience in solution design, programming, and leading teams in ML application development. A comprehensive benefits package is also offered, along with potential performance-based incentives.

Qualifications

• 8+ years of experience designing data-intensive solutions.
• 4+ years of programming experience in Python, Scala, or Java.
• 3+ years of experience with ML systems and production-ready data pipelines.

Responsibilities

• Design and deliver ML models solving real business problems.
• Collaborate with cross-functional Agile teams.
• Maintain, monitor, and improve ML models in production.

Skills

Machine Learning

Python

Distributed Computing

Cloud Solutions

Agile Teamwork

Education

Bachelor's Degree

Master’s or Doctoral Degree in a relevant field

Tools

AWS

TensorFlow

PyTorch

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.

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

Salary and Benefits

The minimum and maximum full‑time annual salaries for this role are listed below by location. Salaries are exclusive to the specified locations and reflect 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.

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer

Other locations will have pay ranges associated with those locations, and the actual annualized salary offered will be reflected 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 may 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. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.

Sponsored Employment Authorization

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

Equal Opportunity and Accommodations

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.

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 1‑800‑304‑9102 or via email at [e-mail]. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.