Quantitative Software Engineer: Techniques Engineering

What you'll do

• Partner with ML researchers on model architectures, training methods, LLM and agentic engineering, and experimental objectives.
• Turn research prototypes into maintainable production code and optimize large-scale training and inference pipelines, including GPU utilization.
• Extend research libraries for agentic workflows and improve codebase structure, testing, and maintainability.

What they ask for

• BS in Computer Science, Mathematics, Physics, or a related technical subject area.
• Experience in quantitative software engineering.
• Strong software engineering skills using Python, AI coding tools, version control, testing frameworks, and CI/CD practices.
• Hands-on experience building high-throughput GPU ML systems, including performance optimization, batching, scheduling, orchestration, and training infrastructure.

Nice to have

• Experience with CUDA and ML frameworks such as PyTorch, TensorFlow, or Hugging Face.
• Experience with LLMs and agent frameworks, agent evaluation, RLHF, RLVR, policy optimization, or synthetic data generation.

Pay

$165,000 and $300,000 (base salary)

Tools

Python, CUDA, PyTorch, TensorFlow, Hugging Face, LLMs, AI coding tools, CI/CD

AI focus

Enable AI/ML modeling research and production, including LLM and agentic workflows, GPU-optimized training and inference, and AI-assisted or AI-generated code.