Thinking Machines Lab · 1 month ago
Research, Post-Training
San Francisco
Full-time
Onsite
Mid, Senior Level
$350K/yr - $475K/yrThinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. The role of post-training researchers sits at the core of our roadmap, blending fundamental research and practical engineering to create AI systems that are useful, safe, and collaborative for humans.
Artificial Intelligence (AI)Foundational AIGenerative AIInformation TechnologyProduct ResearchSoftware
Responsibilities
Develop and tune the recipe: iterate on post-training recipes, consisting of a collection of datasets, training stages, and hyperparameters. Measure how recipe choices affect various metrics
Iterate on evals: post-training involves a never-ending loop of defining a set of evaluations, optimizing them, and then realizing your existing evals don’t capture what matters. You’ll be responsible for both making numbers go up, and making sure the numbers are meaningful
Debug and understand: while tuning the details of a training configuration, we often observe results that don’t quite make sense. You’ll be responsible for both getting things to work, and developing a deeper understanding, which we can bring to the next problem
Scale and explore: post-training will involve a combination of scaling the existing methodologies and developing new ones. We’ll want to both measure how performance metrics scale with dataset size, and explore using a completely different kind of training dataset
Publish and present research that moves the entire community forward. Share code, datasets, and insights that accelerate progress across industry and academia
Qualification
Required
Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX). Comfortable with debugging distributed training and writing code that scales
Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding
Clarity in communication, an ability to explain complex technical concepts in writing
Preferred
A strong grasp of probability, statistics, and ML fundamentals. You can look at experimental data and distinguish between real effects, noise, and bugs
Prior experience with RLHF, RLAIF, preference modeling, or reward learning for large models
Experience managing or analyzing human data collection campaigns or large-scale annotation workflows
Research or engineering contributions in alignment, data-centric AI, or human-AI collaboration
PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience
Benefits
Generous health, dental, and vision benefits
Unlimited PTO
Paid parental leave
Relocation support as needed
Company
Thinking Machines Lab
Thinking Machines Lab is an AI research and product company that aims to increase understanding and customization of AI systems.
Founded in 2025
11-50 employees
H1B Sponsorship
Thinking Machines Lab has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (9)
Funding
Current Stage
Early StageTotal Funding
$2.01BKey Investors
Andreessen HorowitzMinistry of Economy, Culture and Innovation
2025-06-20Seed· $2B
2025-05-05Grant· $9.98M
Leadership Team
Mira Murati
Co-Founder and Chief Executive Officer
Recent News
Morningstar.com
2026-01-11
Business Insider
2026-01-06
Crunchbase News
2026-01-02
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