Thinking Machines Lab
Software Engineer, Research Tools
San Francisco
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
This range already reaches Level IV — the maximum four lottery entries.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Francisco-Oakland-Fremont, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
Employer immigration record
from this employer's Department of Labor filings
Files H-1B transfers
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- We are a team of full stack generalists with strong product instincts who work closely with researchers.
- You'll identify researchers' most important bottlenecks and turn them into reliable, generalizable systems.
- This role requires technical judgment, close cross-functional collaboration, and product intuition.
Responsibilities
- Design, build, and maintain research infra, including evaluation frameworks, training systems, experiment tracking platforms, and visualization tools.
- Work across backend systems, data pipelines, and user-facing applications to deliver tools end to end.
- Partner directly with researchers to identify bottlenecks and unlock new capabilities. Treat research tooling as a product: proactively gather feedback, set priorities, and measure adoption.
- Build systems for reproducibility, traceability, and robust quality control across research experiments and model training runs, with monitoring and observability built in.
- Strong software engineering fundamentals and experience building reliable, maintainable systems.
- Experience collaborating with cross-functional partners and subject-matter experts.
Requirements
- Two years of post-grad work experience as a software engineer or ML engineer, exclusive of internships.
- Proficiency in at least one backend programming language
- Experience working with databases, data warehouses (Clickhouse), caching systems such as Redis, and other data infra.
- Comfort working across the stack and owning projects from initial problem discovery through deployment and operation.
Nice to have
- We encourage you to apply even if you meet only some of these:
- Experience working closely with researchers to understand and solve their tooling needs.
- Visa sponsorship: We sponsor visas.
- 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.
Compensation
- Depending on background, skills and experience, the expected annual salary range for this position is $300,000 - $350,000 USD.
Benefits
- Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
- A bachelor's degree, or equivalent practical experience, in computer science, engineering, machine learning, or a related field.
Company info
- ABOUT THE ROLE We are a team of full stack generalists with strong product instincts who work closely with researchers.
- The mission of Thinking Machines is to build AI that extends human will and judgment.
- We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication.
Visa & Work Authorization
- We sponsor visas.
- 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.
This listing is sourced directly from Thinking Machines Lab's careers page and normalized into a canonical job model.