Lead AI Engineer role focused on vision model customization and VLM, building responsible, reliable AI systems end to end.

Work with a cross-functional group of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associates and customers.
Design, develop, test, deploy, and support AI software components across production workflows, including:
- Foundation model training
- Large language model inference
- Similarity search and vector database applications
- Guardrails
- Model evaluation
- Experimentation, governance, and observability
- Additional related AI components
Build using a mix of open source and SaaS AI technology, including AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch.
Develop and introduce state-of-the-art LLM optimization methods to improve scalability, cost, latency, and throughput for large-scale production AI systems.
Help shape the technical direction and long-term roadmap for foundational AI systems.

Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master’s degree plus at least 2 years of experience developing AI and ML algorithms or technologies.
At least 4 years of programming experience with Python, Go, Scala, or Java.

Performance-based incentive compensation, potentially including cash bonus(es) and/or long-term incentives (LTI).
Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being.

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 optimization techniques for training and inference software to improve hardware utilization, latency, throughput, and cost.
Interest in staying current with AI research and AI systems, with a focus on applying novel techniques in production.

Location: McLean, VA 22101 (onsite)

Compensation: USD 197,300 - 225,100 per year

Lead AI Engineer (Vision model customization, VLM)

Job Description