Research, Post-Training Data

Thinking Machines Lab
San Francisco
Workplace: HybridFull timeUSD 350,000 - 475,000 annuallyFunction: Education & TrainingEducation: bachelorsSkills: ["Communication","Scientific rigor","Debugging","Technical writing","Experimentation"]

Build and evaluate post-training data systems at the intersection of human insight and machine learning. Design data collection, synthesis, and labeling pipelines (including model-assisted and synthetic data), research human preferences and behavior, and iteratively improve evaluation methods and quantitative metrics. Contribute both high-performance code and research outputs, helping make post-training interventions safer, more aligned, and more useful for humans.

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Thinking Machines Lab
Thinking Machines Lab
1 day ago

Research, Post-Training Data

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Last checked: 9 hours agoStatus: Live

Job Summary

Build and evaluate post-training data systems at the intersection of human insight and machine learning. Design data collection, synthesis, and labeling pipelines (including model-assisted and synthetic data), research human preferences and behavior, and iteratively improve evaluation methods and quantitative metrics. Contribute both high-performance code and research outputs, helping make post-training interventions safer, more aligned, and more useful for humans.
Location: San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Education & Training

Key Responsibilities

  • •Design and execute data collection and synthesis strategies for post-training using human feedback, preference data, and synthetic examples.
  • •Develop pipelines and frameworks for scalable, high-quality human labeling, model-assisted labeling, and synthetic data generation.
  • •Research and model human preferences and behavior to improve reasoning, truthfulness, and helpfulness.
  • •Iterate on post-training evaluations, optimizing and ensuring metrics remain meaningful.
  • •Design and evaluate metrics and benchmarks for data quality, alignment, and real-world impact; publish and present research with code and datasets.

Pay and Benefits

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

Key Requirements

  • •Strong engineering skills to contribute code and debug complex codebases.
  • •Experience with data curation, human feedback, or synthetic data generation for large language models or similar systems.
  • •Ability to design, run, and interpret experiments with scientific rigor and clarity.
  • •Proficiency in Python and familiarity with PyTorch, TensorFlow, or JAX; comfortable debugging distributed training and scaling code.
  • •Bachelor’s degree (or equivalent) in Computer Science, Machine Learning, Physics, Mathematics, or related fields with strong theoretical and empirical grounding.
Experience:Machine learningLarge language modelsHuman feedbackSynthetic dataResearch
Education:Bachelor's
Skills:CommunicationScientific rigorDebuggingTechnical writingExperimentation
Tech Stack:PythonPyTorchTensorFlowJAXDeep learningDistributed 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