Lead Machine Learning Engineer Job at Capital One (San Francisco)

Job Description

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Job Responsibility

Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with a cross-functional team of engineers, research scientists, technical program managers, and product managers.
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
Construct optimized data pipelines to feed ML models.
Design, develop, test, deploy, and support AI software components including large language model inference, similarity search, model evaluation, experimentation, governance, and observability, etc.
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.

Requirements

Bachelor’s Degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems

Nice to have

Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
Experience developing, delivering, and supporting ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
2+ years of experience with data gathering and preparation for ML models
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory)
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
Ability to communicate complex technical concepts clearly to a variety of audiences

What we offer

performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

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Lead Machine Learning Engineer

Job Description

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Requirements

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