Sr. Distinguished Engineer
Listed on 2026-07-15
-
Software Development
Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Overview:
As a Capital One Machine Learning Engineer, you will provide technical leadership to engineering teams focused on product ionizing machine learning applications and systems will participate in detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You will serve as a technical domain expert in machine learning, guiding architectural design decisions, reviewing model and application code, and ensuring high availability and performance of our machine learning applications.
You will have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering, 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 7 years of experience programming in C, C++, Python, or Scala
- At least 4 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
- 3+ years of experience using Dask, RAPIDS, or in High Performance Computing
- 3+ 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
McLean, VA: $314,800 – $359,300 for Sr Distinguished Machine Learning Engineer
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.
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.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).