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About the Role

This role is responsible for advancing the agentic capabilities of our models, with ownership spanning the full development cycle. The research team is small, and the role carries a corresponding degree of autonomy and responsibility.

Responsibilities

• Build a synthetic data framework used across the team, and create new task environments to scale training across agentic capabilities such as tool use, long-horizon tasks, and complex workflows.
• Address identified gaps through data and recipe work, validating proposed changes through controlled ablations.
• Enhance usability for agent capabilities end to end, translating internal and external feedback into model improvements.

Requirements

• Strong engineering skills, ability to contribute code and debug in complex codebases.
• Ability to design, run, and interpret experiments with scientific rigor and clarity.
• 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.
• Experience building synthetic data pipelines and systems that were adopted by others on your team and remain in use today.
• Experience owning the end-to-end cycle of identifying gaps in model usability and closing them through custom evaluations and training data.
• Experience making large-scale agentic RL infrastructure reliable given the long tail of failures that surface at scale.
• Experience improving the agentic capabilities of a frontier model.
• PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience.

Skills

• Python
• PyTorch
• TensorFlow
• JAX

Location

• San Francisco, California

Work Type

• Onsite

Experience Level

• Bachelor’s degree or equivalent experience
• PhD or equivalent industry research experience

Education Level

• Bachelor's degree in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline
• PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline

Salary/Compensations

• $350,000 - $475,000 USD

Benefits

• Generous health, dental, and vision benefits
• Unlimited PTO
• Paid parental leave
• Relocation support

About the Company

• The mission of Thinking Machines is to build AI that extends human will and judgment.
• We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication.
• We believe the future worth building is human, and we're hiring people who want to build it.