Machine Learning Engineering Technical Leader

What you'll do

• Own the lifecycle of AI research and deployment, from model design and evaluation through production rollout.
• Set the scientific roadmap for agentic GenAI and advance DSL-aware code synthesis and scalable training and inference.
• Partner with engineering and product, mentor researchers, and shape AI strategy and technical direction.

What they ask for

• PhD in a related technical field plus 5+ years of post-doctoral or industry experience; or a Master’s degree in a related field plus 10+ years of industry experience.
• 3+ years developing Large Language Models (LLMs) for program synthesis or formal languages.
• 2+ years in multi-step planning or agentic AI for developer workflows.
• 3+ years with Python and deep learning frameworks such as PyTorch or TensorFlow, and 3+ years translating research prototypes into production systems.

Nice to have

• Strong foundation in experimental design, benchmarking, reproducibility, evaluation metrics, and scientific documentation.
• Experience with code-generation LLMs, structured-language modeling, agentic AI, large-scale training and optimization, MLOps, or research leadership.

Pay

$234,400.00 to $296,600.00 USD (base salary); $256,900.00 - $383,500.00 USD (base salary, New York City Metro Area); $234,400.00 - $341,100.00 USD (base salary, Non-Metro New York state & Washington state)

Tools

Python, PyTorch, TensorFlow, Code-LLaMA, CodeT5, StarCoder, GPT

AI focus

Research and deploy GenAI systems for code generation, including agentic planning, tool use, DSL-aware synthesis, and scalable model training and inference.