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Software Engineer, Inference

Thinking Machines Lab · San Francisco, California

Location
San Francisco, California, United States
Employment
Full time
Level
Mid level
Posted
Today

About this role

About Thinking Machines

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. We believe the future worth building is human, and we're hiring people who want to build it.

About the Role

We're hiring a Software Engineer, Inference to own the reliability, scale, and efficiency of the systems that serve our models to real users. Our research and inference teams push the limits of model performance and serving efficiency; this role makes sure those gains reach production safely and stay up - powering Tinker's live, multi-tenant serving and the products built on top of our models.

This is a production-facing systems role at the center of the company. You'll be the bridge between cutting-edge inference techniques and the day-to-day reality of serving real traffic: rollouts, capacity, incidents, and everything that keeps a fast-growing platform online.

What You'll Do

  • Operate and scale the production inference systems that serve live traffic, including Tinker's multi-tenant serving platform

  • Own the rollout process for new models, model versions, and inference optimizations, ensuring safe, incremental deployment to production

  • Build and improve observability, alerting, and capacity planning so the team can detect, diagnose, and resolve production issues quickly

  • Partner with inference and research teams to productionize new serving techniques without compromising reliability

  • Lead incident response for production inference issues, driving root cause analysis and durable fixes

  • Design for graceful degradation, failover, and redundancy so that serving stays resilient as usage grows

  • Manage capacity and cost tradeoffs for serving infrastructure as traffic and model sizes scale

Skills & Qualifications

Minimum Qualifications

  • Experience operating large-scale, latency-sensitive production systems

  • Proficiency in Python and Go or another systems language

  • Experience with observability, monitoring, and incident response for production services

  • Strong understanding of distributed systems and how they fail at scale

Preferred Qualifications

  • Experience running production inference for large language models or other large-scale ML systems

  • Experience with deployment and rollout systems, such as canarying, blue/green deploys, or feature flags

  • Experience with capacity planning and cost optimization for GPU or TPU infrastructure

  • Familiarity with inference-specific techniques, such as batching, caching, or quantization, and their operational implications

  • Comfortable being on-call and leading incident response for critical production systems

  • Comfortable working with high autonomy in a fast-changing, early-stage environment

Logistics

  • Location: This role is based in San Francisco, CA.

  • Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $300,000 - $400,000 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 published by Thinking Machines Lab. Applications are handled on their site.

Skills this posting mentions

GPUInfrastructureObservability

About Thinking Machines Lab

Thinking Machines Lab is an artificial intelligence research and product company. We’re building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.

All 55 openings at Thinking Machines Lab

One click, then it is written

Apply to Thinking Machines Lab with a resume written for this role.

Queue Software Engineer, Inference and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Thinking Machines Lab’s form for you.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

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    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

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Paste your career in once. Every application after that is written for you.

Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.

  1. 01Drop your resume

    A PDF or a LinkedIn URL. About a minute, once.

  2. 02I rank the openings

    Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.

  3. 03Each one is written up

    Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.

  • New matches ranked and written before you are up.
  • Every bullet stays inside what your history supports. Nothing invented.
  • Queued, submitted, interviewing, offer: one screen, not a spreadsheet.

500 free credits on sign-up. No card. Nothing is sent until you say so.

Listed from the job board Thinking Machines Lab publishes. Refolk is not the employer and does not handle their hiring. Applications go to Thinking Machines Lab directly.