Distinguished Machine Learning Engineer

Distinguished Machine Learning Engineer

As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams dedicated to product ionizing machine learning applications and systems ’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring 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. You’ll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.

• Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
• Drive the creation and evolution of ML models and software that enable state‑of‑the‑art intelligent systems
• Lead large‑scale ML initiatives with the customer in mind
• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
• Optimize data pipelines to feed ML models
• Use programming languages like Python, Scala, C/C++
• Leverage compute technologies such as Dask and RAPIDS
• Evangelize best practices in all aspects of the engineering and modeling life cycles
• Help recruit, nurture, and retain top engineering talent

• Bachelor’s degree
• At least 10 years of experience designing and building data‑intensive solutions using distributed computing
• At least 6 years of experience programming in C, C++, Python, or Scala
• At least 3 years of experience with the full ML development lifecycle using modern technology in a business‑critical setting

• Master’s Degree
• 3+ years of experience designing, implementing, and scaling production‑ready data pipelines that feed ML models
• 2+ years of experience using Dask, RAPIDS, or in High Performance Computing
• 2+ years of experience with the PyData ecosystem (Num Py, Pandas, and Scikit‑learn)
• Ability to communicate complex technical concepts clearly to a variety of audiences
• ML industry impact through conference presentations, papers, blog posts, or open source contributions
• Ability to attract and develop high‑performing software engineers with an inspiring leadership style

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

• McLean, VA: $269,100 - $307,200
• New York, NY: $293,600 - $335,100
• Cambridge, MA: $269,100 - $307,200
• San Francisco, CA: $293,600 - $335,100
• San Jose, CA: $293,600 - $335,100

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. 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 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.