Forward Deployed Engineer, Tinker

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 Tinker Tinker is our fine-tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs. Tinker is rapidly adding new customers, features, and novel use-cases. We’re hiring to grow the platform alongside the Tinker community. About the Role We're hiring a Forward Deployed Engineer to be the main point of contact with our customers, which range from individual hackers to major enterprises. You will diagnose their problems and needs and turn those into product improvements, taking ownership of both ends of this process. What You’ll Do Triage and resolve customer issues across the full stack, reading logs, reproducing failures, and tracing job execution. Build tools, integrations, and automation that eliminate recurring failure modes and reduce time-to-resolution for users. Write and maintain high-quality documentation and cookbook recipes, grounded in real issues and implementations from our users. Partner closely with research and infrastructure teams to translate customer pain into prioritized engineering work. Inform Tinker's product roadmap based on what you learn from working directly with customers every day. Skills and Qualifications Minimum qualifications: Bachelor's degree or equivalent experience in computer science, engineering, or similar. Experience fine-tuning large language models with supervised and reinforcement learning methods. Experience debugging distributed systems and training infrastructure: reading logs, tracing job failures, diagnosing GPU, networking, or scheduling issues. Proficiency in at least one backend language (we use Python and Rust). Preferred qualifications — we encourage you to apply if you meet some but not all of these: 5+ years of software engineering experience, including work in customer-facing or deployment roles. Building or shipping a product end-to-end — a startup, an open-source project, or an internal tool you owned from idea to users. Published technical tutorials, recipes, or documentation that helped others get unstuck. Experience at a developer tools, API-first, or ML platform company. Familiarity with hyperparameter tuning for LLM training algorithms. Contributions to open-source ML or infrastructure projects. 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 $350,000 - $475,000 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. ... (truncated, view full listing at source)