AI Lead at Aspire Software identifying and scaling AI - powered products. Engaging with customers through direct interaction and iterations based on real - world feedback.
About the role
- Lead AI Engineer at Capital One partnering with cross-functional teams to deliver AI-powered banking products. Responsible for designing, developing, and supporting AI software components.
Responsibilities
- Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
- 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, etc.
- Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
- 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.
Requirements
- 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
- 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
Benefits
- 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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