Member of Technical Staff – ML Engineering (AI)

Location: Cambridge, Massachusetts; hybrid with three days onsite per week. US citizenship or a Green Card is required.

Salary: $200,000–$350,000 annually.

Company

Build infrastructure for an AI research company developing autonomous AI systems to accelerate scientific discovery through hypotheses, simulations, and scientific testing.

What you will do

• Build and maintain production ML infrastructure for advanced AI research.
• Develop scalable distributed training, inference serving, ML platform, and agent evaluation systems.
• Turn experimental research code into reliable, maintainable production services.
• Optimize model serving, infrastructure performance, and system reliability.
• Debug complex production failures across distributed ML workloads.
• Collaborate with ML researchers to accelerate experimentation and model deployment.

Requirements

• At least 3 years of hands-on experience building or operating production ML training or inference infrastructure.
• Strong software engineering background and experience building systems used by engineers or researchers.
• Deep expertise in at least one of distributed ML training infrastructure, inference optimization and model serving, ML platforms and infrastructure, or agent and evaluation infrastructure.
• Proven ability to debug and resolve production infrastructure issues.
• Strong programming and systems engineering capabilities.
• Ability to work onsite in Cambridge three days per week.
• US citizenship or Green Card required.

Nice to have

• Experience with PyTorch, Kubernetes, Ray, vLLM, CUDA, or GPU infrastructure.
• Experience across multiple ML infrastructure specialisms.
• GPU performance optimization or distributed systems expertise.
• Direct collaboration experience with ML researchers.

Culture & Benefits

• Work on infrastructure supporting AI research and scientific discovery.
• High technical ownership and direct exposure to advanced research.
• Collaborate with researchers and engineers on next-generation AI systems.
• Highly competitive compensation with flexibility for exceptional candidates.

Hiring process

• Apply to learn more about the team, research, and engineering challenges.