# Research, General Agents

**Company:** [Thinking Machines Lab](https://hotfix.jobs/companies/thinking-machines-lab)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Salary:** $350k – $475k/yr
**Skills:** Python, PyTorch, TensorFlow, JAX, Distributed Training, Synthetic Data Pipelines, Reinforcement Learning, Model Evaluation, Deep Learning, Scientific Experimentation
**Posted:** 2026-08-27

> Research-focused engineer advancing agentic model capabilities across synthetic data, task environments, evaluations, training, and usability improvements. Requires strong Python engineering, deep learning framework experience, scalable distributed training skills, and scientific experimentation ability.

## Job Description

## Responsibilities
- Build a synthetic data framework used across the team.
- Create task environments to scale training for agentic capabilities, including tool use, long-horizon tasks, and complex workflows.
- Address model capability gaps through data and recipe development, validating proposed changes with controlled ablation studies.
- Improve agent usability end to end by translating internal and external feedback into model improvements.

## Requirements
- Strong software engineering skills, including the ability to contribute code and debug 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 such as PyTorch, TensorFlow, or JAX.
- Experience debugging distributed training and writing scalable code.
- Bachelor’s degree or equivalent experience in computer science, machine learning, physics, mathematics, or a related discipline.
- Clear written communication and the ability to explain complex technical concepts.

## Nice-to-haves
- Experience building synthetic data pipelines and systems adopted and maintained by a team.
- Experience identifying model usability gaps and addressing them through custom evaluations and training data.
- Experience making large-scale agentic reinforcement-learning infrastructure reliable.
- Experience improving the agentic capabilities of a frontier model.
- PhD in computer science, machine learning, physics, mathematics, or a related discipline, or equivalent industry research experience.

## Compensation and Benefits
- Expected annual salary: $350,000–$475,000 USD.
- Health, dental, and vision benefits.
- Unlimited paid time off.
- Paid parental leave.
- Relocation support.
- Visa sponsorship may be available.

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