Distinguished Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other material to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization.

About the Team: 

The Capital One machine learning platform foundation organization manages our cloud-based enterprise AI+ML system delivering the high-scale developer and runtime environments required to build, orchestrate, and deploy compute and data intensive AI systems across real-time and batch workloads. We are seeking a  Distinguished Engineer, a hands-on technical leader passionate about distributed systems, to engineer and scale foundational compute capabilities for our platform.

You will use your experience in building large scale, highly available and high performance systems to develop our common compute infrastructure on top of CPU and GPU substrates. Your contributions will power everything from developer notebooks to ML / DL model training, model inference and feature generation pipelines to pre-training and fine tuning Transformer-based models as well as generative AI inference and agentic applications. Your depth of expertise in technologies including Golang and Python programming languages, popular distributed compute frameworks including Spark / Dask / Ray / Flink, container (e.g., Kubernetes) and serverless (e.g., AWS Lambda) runtime environments, and ML+AI workload patterns will provide an amplifying technical element that is paramount to our team's success.

What you’ll do:

• Architect and build control and data plane implementations required to realize a highly available, multi-tenant, large scale and a secure machine learning platform

• Develop Ray and Spark distributed compute engine solutions to accelerate diverse workloads from LLM pre-training and reinforcement learning to large-scale data processing, while maximizing compute unit economics

• Engineer systemic improvements for operational excellence including automating KTLO (Keep The Lights On) workflows

• Direct the technical execution of a diverse project portfolio, collaborating with developers specializing in everything ranging from distributed microservices to running large foundation models

• Work cross-functionally with product and program management disciplines, and stakeholder and partners across Capital One to help optimize business outcomes while driving towards strong technology solutions

• Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and leading system design and code review sessions

• Help elevate the Capital One Distinguished Engineering community and establish yourself as a go-to resource on given technologies and technology-enabled capabilities

• Lead the way in creating next-generation talent, mentoring internal talent and actively recruiting external talent to bolster the Capital One tech talent pool

Responsibilities:

• Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in

• Strike the right balance between lending expertise and providing an inclusive environment where others’ ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team

• Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible

• Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization

• Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an unified manner

• Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One’s Tech talent

Basic Qualifications

• Bachelor’s Degree

• At least 7 years of experience in software engineering 

• At least 7 years of experience designing distributed systems, backend architecture, and API platforms

• At least 5 years of experience with public cloud technologies
   

Preferred Qualifications:  

• A Master’s Degree in Computer Science or a Master’s Degree in Software Engineering

• 3+ years of experience building platforms that support LLM training, fine-tuning, or high-throughput inference

• 3+ years of experience with AWS-specific compute primitives (EKS, EC2 UltraClusters, Graviton) and cost-optimization strategies

• 3+ years of experience with building platforms at scale and experience with distributed computing frameworks such as Spark and Ray

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.

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.

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. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.