Capital One
banking
LeadAI/MLEngineer(Platform,kubeflow)
“Lead AI/ML Engineer (Platform, kubeflow) at Capital One. Skills: AI/ML Platform, kubeflow, Large Language Models (LLMs), AI Software Development, System Design, Optimization Techniques. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. Invent and introduce state-of-the-art LLM optimization techniques to improve the p”
What You'll Achieve.
deliver AI-powered products that change how our associates work and how our customers interact with Capital One; deliver value to millions of customers; enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact; reimagine how we serve our customers and businesses
Industry & Context.
bring clarity to big, undefined problems; digging deep to uncover the root of problems
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies, At least 4 years of experience programming with Python, Go, Scala, or Java
Nice to Have
6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud), Experience designing, developing, delivering, and supporting AI services, Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang, Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost, Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
What You'll Do.
and support AI software components including foundation model training
large language model inference
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability
throughput — of large scale production AI systems
Contribute to the technical vision and the long term roadmap of foundational AI systems
How You'll Work.
Team & Collaboration
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
Communication Scope
articulate your findings concisely with clarity; share new ideas
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