Research, Post-Training

Thinking Machines Lab
San Francisco
Workplace: HybridFull timeUSD 350,000 - 475,000 annuallyFunction: Education & TrainingEducation: bachelorsSkills: ["Communication"]

Shape how AI learns by driving post-training research end-to-end—developing and tuning training “recipes,” iterating on evaluations, debugging training runs, and scaling methods across dataset sizes. You’ll combine deep theoretical thinking with hands-on experimentation, and publish shareable research outputs (code, datasets, insights) that improve safety and collaboration for humans.

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Thinking Machines Lab
Thinking Machines Lab
23 hours ago

Research, Post-Training

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Source: Company careers pageValidated by: Fursa AI
Last checked: 9 hours agoStatus: Live

Job Summary

Shape how AI learns by driving post-training research end-to-end—developing and tuning training “recipes,” iterating on evaluations, debugging training runs, and scaling methods across dataset sizes. You’ll combine deep theoretical thinking with hands-on experimentation, and publish shareable research outputs (code, datasets, insights) that improve safety and collaboration for humans.
Location: San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Education & Training

Key Responsibilities

  • •Develop and tune post-training recipes (datasets, training stages, hyperparameters) and measure impact on metrics.
  • •Iterate on evaluations to optimize what matters and ensure eval results are meaningful.
  • •Debug and investigate unexpected outcomes while tuning training configurations.
  • •Scale existing post-training methodologies and explore new training datasets and approaches.
  • •Publish and present research by sharing code, datasets, and insights with industry and academia.

Pay and Benefits

Salary: USD 350,000 - 475,000 annually
Perks:Health InsuranceDentalVisionPaid LeavePaid ParentalRelocation

Key Requirements

  • •Proficiency in Python and familiarity with at least one deep learning framework (PyTorch, TensorFlow, or JAX), with comfort debugging distributed training.
  • •Bachelor’s degree (or equivalent experience) in Computer Science, Machine Learning, Physics, Mathematics, or a related field with strong theoretical and empirical grounding.
  • •Ability to clearly communicate complex technical concepts in writing.
  • •Strong grasp of probability, statistics, and ML fundamentals to distinguish real effects, noise, and bugs.
  • •Experience with RLHF, RLAIF, preference modeling, or reward learning for large models.
Experience:AI researchMachine learning
Education:Bachelor's
Skills:Communication
Tech Stack:PythonPyTorchTensorFlowJAXDistributed training

Eligibility

Work Authorization:Sponsorship available.

Company Brief

Thinking Machines Lab
Develops enterprise AI solutions, custom large language models, and ML platforms to help organizations deploy intelligent applications. Services include data engineering, model development, and AI consulting for scale and production readiness.
Industry: AI & Machine Learning
Company Size: Medium (51 to 250 employees)
Growth: Growth Stage Startup
Headquarters: Mumbai, India
Website