Thinking Machines Lab
Research Infrastructure Engineer, Research Acceleration
San Francisco
H1B sponsorship available$350k-$475kDetected 21 days ago
PythonRustDistributed SystemsMachine LearningPyTorchSparkLogisticsResearchWriting
About the role
- You will work directly with researchers to identify bottlenecks and pain points.
- Success means researchers trust your systems to just work and find them a delight to use.
Responsibilities
- Design, build, and operate research infrastructure including evaluation frameworks, RL training systems, experiment tracking platforms, visualization tools, and shared utilities.
- Develop high-throughput, scalable pipelines for distributed evaluation, reward modeling, and multimodal assessment.
- Build systems for reproducibility, traceability, and robust quality control across research experiments and model training runs. Implement monitoring and observability.
- Partner directly with researchers to identify bottlenecks and unlock new capabilities. Own research tooling like a product manager, proactively seeking feedback and tracking adoption.
- Collaborate with infrastructure, data, and product teams to integrate tools across the technical stack.
- Strong software engineering fundamentals with a track record of building reliable, maintainable systems.
- Experience in highly collaborative environments involving many different cross-functional partners and subject matter experts.
- Track record building tooling for researchers that achieved high adoption without top down mandates.
Requirements
- Proficiency in at least one backend language (we use Python or Rust).
- Comfort operating across the stack and owning projects end-to-end.
Nice to have
- we encourage you to apply if you meet some but not all of these:
- Contributions to open-source ML tools or widely-used internal frameworks at research-focused organizations.
- Record of publications or technical writing on ML systems, infrastructure, or tooling.
- Background working closely with ML researchers to understand and solve their tooling needs.
- Familiarity with distributed systems, modern ML frameworks (PyTorch, JAX), and data processing at scale.
- Experience with research observability tools, distributed compute frameworks (Ray, Spark), or large-scale evaluation pipelines.
Skills
- Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence.
Compensation
- Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
Benefits
- Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
- Bachelor's degree or equivalent experience in computer science, engineering, machine learning, or similar.
Visa & Work Authorization
- While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
- We sponsor visas.
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This listing is sourced directly from Thinking Machines Lab's careers page and normalized into a canonical job model.