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 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 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.

About the team: 

As part of FS AI labs you will be working on AI initiatives within Financial Services with a focus on Applied AI and Machine Learning (AI/ML), Generative AI, Natural Language Processing (NLP), and Responsible AI. The primary objective of FS AI Labs is to drive the research and delivery of innovative AI and ML use cases that leverage these cutting-edge technologies. You will work on exploring new frontiers, build prototypes, and deliver transformative AI use cases that drive Capital One Financial Services business growth and enhance customer experience.

What you’ll do in the role:

• 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 lifecycles

• Help recruit, nurture, and retain top engineering talent

Basic Qualifications:

• 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

Preferred Qualifications:

• 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 (NumPy, Pandas, and Scikit-learn)

• Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM fine-tuning, LLM Evaluation.

• Experience developing AI and ML algorithms in Python or C/C++

• Experience with building LLM based chatbots in production including experience with developing multi turn and agentic workflows and LLM pre training.

• Experience leveraging a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs,

• 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.

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 agree