Research, Pre-Training Science

Thinking Machines Lab
San Francisco
Workplace: HybridFull timeUSD 350,000 - 475,000 annuallyFunction: Education & TrainingEducation: bachelorsSkills: ["Research judgment","Empirical rigor","Communication","Collaboration","Analytical thinking"]

Advance the science of how large models learn from data by exploring pre-training methods, architectures, and learning objectives. You’ll develop new methodologies for pre-training, design data curricula and sampling strategies, and run scalable, reproducible experiments. The role blends fundamental research with high-performance engineering—writing code, debugging distributed training, and publishing findings. This evergreen position supports ongoing openings in this research area.

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Thinking Machines Lab
Thinking Machines Lab
20 hours ago

Research, Pre-Training Science

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Last checked: 5 hours agoStatus: Live

Job Summary

Advance the science of how large models learn from data by exploring pre-training methods, architectures, and learning objectives. You’ll develop new methodologies for pre-training, design data curricula and sampling strategies, and run scalable, reproducible experiments. The role blends fundamental research with high-performance engineering—writing code, debugging distributed training, and publishing findings. This evergreen position supports ongoing openings in this research area.
Location: San Francisco
Workplace: Hybrid
Employment Type: Full time
Job Function: Education & Training

Key Responsibilities

  • •Research and develop new methodologies for pre-training.
  • •Work on scaling, architecture, algorithms, or optimization for large-scale training runs.
  • •Design data curricula and sampling strategies to improve learning dynamics and generalization.
  • •Collaborate with infrastructure and data teams to run large-scale experiments efficiently and reproducibly.
  • •Publish and present research, 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

  • •Ability to design, run, and analyze experiments with research judgment and empirical rigor.
  • •Experience with distributed or high-performance computing environments.
  • •Proficiency in Python and familiarity with at least one deep learning framework (PyTorch, TensorFlow, or JAX), including debugging distributed training.
  • •Bachelor’s degree (or equivalent experience) in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.
  • •Clear written communication to explain complex technical concepts.
Experience:Machine learningLarge-scale trainingDistributed computingFoundation model research
Education:Bachelor's
Skills:Research judgmentEmpirical rigorCommunicationCollaborationAnalytical thinking
Tech Stack:PythonPyTorchTensorFlowJAXDistributed trainingHigh-performance computingLarge-scale 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