Lead AI Engineer (FM Hosting, LLM Inference)
$197,300–$225,100 year
On-siteMcLean, Virginia, United States
Job Summary
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. Partner with cross-functional teams of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products. Invent and introduce state-of-the-art LLM optimization techniques to improve scalability, cost, latency, and throughput of large-scale production systems. Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.
Required Qualifications
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
- At least 4 years of experience developing AI and ML algorithms or technologies
- Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
- 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
Desired Qualifications
- 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
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