Thinking Machines Verified

["Supercomputing","Artificial Intelligence","Computer Hardware","High-Performance Computing"]

Engineering Manager

San Francisco, California, United StatesFull TimeManager / Head$400,000–$500,000 /yrPosted 2 months ago

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Role summary

We are seeking an Engineering Manager to lead a team of senior and staff-level engineers focused on ML infrastructure and product. This role involves building and scaling reliable, performant, and operable systems. Responsibilities include setting technical direction, owning execution, contributing to system design and debugging, partnering with product and research teams on roadmaps, hiring senior talent, and mentoring engineers. The ideal candidate has a Bachelor's degree or equivalent experience, 8+ years in production systems, and 3+ years of engineering management experience in high-growth environments. Familiarity with AI/ML systems, data infrastructure, or developer productivity is preferred.

Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.

We are scientists, engineers, and builders who’ve created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.

About the Role

We're hiring an Engineering Manager to lead a team of senior and staff-level engineers across ML infrastructure and product. You will help the team build and scale systems that are reliable, performant, and easy to operate.

This role combines collaboration with hand-on work. You’ll partner with tech leads to set the technical direction for your team and own its execution. You should also be ready to go deep on system design and contribute directly when needed.

What You’ll Do

Lead and grow a team of senior and staff-level engineers, setting clear expectations and maintaining a high bar for execution.

Own architecture, system design, and long-term technical direction for your team's systems, with emphasis on reliability and performance.

Contribute directly to design reviews, prototyping, and debugging critical issues.

Partner with researchers and product teams to define roadmaps and prioritize work.

Hire and close senior engineering talent. Mentor engineers into technical leaders.

Skills and Qualifications

Minimum qualifications:

Bachelor’s degree or equivalent industry experience in computer science, engineering, or similar.

8+ years of experience building and scaling production systems, including system design and distributed systems.

3+ years of engineering management experience in high-growth environments.

Preferred qualifications — we encourage you to apply even if you don’t meet all preferred qualifications, but at least some:

Experience managing teams of senior or staff-level engineers.

Background in infrastructure, systems engineering, or developer productivity.

Familiarity with AI/ML systems, data infrastructure, or high-performance computing.

Track record of building or contributing to widely used systems, platforms, or tools.

Logistics

Location: This role is based in San Francisco, California.

Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $400,000 - $500,000 USD.

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.

Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

Thinking Machines Lab will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the California Fair Chance Act, the San Francisco Fair Chance Ordinance, and any other applicable state or local fair chance ordinance or law.

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