Machine Learning Engineer

Member of Technical Staff – ML Engineering

Cambridge, Massachusetts | Hybrid (3 days onsite)

Compensation: Highly competitive and flexible for exceptional candidates

Build the infrastructure behind the next generation of scientific AI.

We're working with an ambitious AI research company developing autonomous AI systems designed to accelerate scientific discovery.

Their vision is to build an AI-native research laboratory where intelligent systems can formulate hypotheses, run simulations and test scientific ideas against the laws of physics.

They're looking for a Member of Technical Staff (ML Engineering) to build the infrastructure that bridges cutting-edge machine learning research and dependable production systems.

This is an opportunity to work directly with AI researchers, solve complex engineering problems and take genuine ownership of critical ML infrastructure.

What you'll be doing

• Build and maintain production ML infrastructure supporting advanced AI research.
• Develop scalable distributed training, inference serving, ML platform or 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.
• Work closely with researchers to accelerate experimentation and model deployment.

What we're looking for

Must-haves:

• 3+ years of hands-on experience building or operating production ML training or inference infrastructure.
• Strong software engineering background, with experience building systems used by other engineers or researchers.
• Deep expertise in at least one of the following:
• Distributed ML training infrastructure
• Inference optimization and model serving
• ML platforms and infrastructure
• Agent and evaluation infrastructure
• Proven experience debugging and resolving 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-haves:

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

Why consider this opportunity?

• Work on infrastructure supporting ambitious AI research and scientific discovery.
• Solve challenging problems across distributed systems, model training and inference.
• High technical ownership with direct exposure to cutting-edge research.
• Work alongside researchers and engineers building next-generation AI systems.
• Highly competitive compensation, with flexibility for exceptional talent.

Location: Cambridge, MA (3 days onsite)

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