Capital One - Plano, TX

posted 3 months ago

Full-time - Senior
Plano, TX
Credit Intermediation and Related Activities

About the position

At Capital One, we believe that machine learning represents the biggest opportunity in financial services today, and is a chance to revolutionize the industry. Capital One's commitment to machine learning has sponsorship from the CEO, the Board of Directors, and the executive committee of the company. The Center for Machine Learning is at the heart of this effort, and is leading the way towards building responsible and impactful tools, platforms, and solutions that leverage ML. 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. 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.

Responsibilities

  • Lead large-scale ML initiatives with the customer in mind.
  • Lead the development of AI and ML use cases that leverage state of art AI and ML techniques, working in collaboration with the Product, Architecture, Engineering, and Data Science teams.
  • Stay abreast of the latest advancements in Generative AI, Large Language Models, NLP.
  • Drive research efforts to identify new opportunities and use cases, pushing the boundaries based on feasibility.
  • Collaborate with business stakeholders to understand the needs and identify opportunities where AI can be applied.
  • Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
  • Evangelize best practices in all aspects of the AI/ML engineering and modeling lifecycles.
  • Help recruit, nurture, and retain top engineering talent.

Requirements

  • 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.
  • At least 2 years of experience using Dask, RAPIDS, or in High Performance Computing.
  • At least 2 years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn).

Nice-to-haves

  • Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques.
  • 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 partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms.
  • Experience leveraging a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
  • 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.

Benefits

  • Comprehensive health benefits
  • Financial benefits
  • Inclusive set of benefits that support total well-being
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service