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Research, Finetuning Science

Thinking MachinesSan FranciscoResearch
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Salary
$350K - $475K USD
Job type
Full-time
Posted
16 Sept 2026
Status
Open · checked 7d ago

About this role

The Research, Finetuning Science role at Thinking Machines is a full-time position based in San Francisco, California, with remote flexibility available. This opportunity suits professionals with a strong background in machine learning and Python who want to advance frontier customization techniques and build industry-leading post-training engines.

Role Overview

Thinking Machines is seeking a dedicated researcher to work on frontier customization techniques and help construct a top-tier post-training engine named Tinker, utilizing a comprehensive understanding of reinforcement learning science. In this capacity, daily discoveries directly influence Tinker's training defaults, API design, and the open-source Tinker Cookbook. Personnel will collaborate directly with internal research groups while actively contributing to open science initiatives alongside external partners.

Key Responsibilities

Advance the overall science of fine-tuning and frontier post-training methods.
Focus on areas such as LoRA and parameter-efficient fine-tuning to maximize customization quality, efficiency, and reliability at the frontier.
Translate research directly into products by shaping training defaults, shaping primitives, and codifying best-practice recipes inside the Tinker Cookbook.
Enhance the stability, efficiency, and overall reliability of large-scale fine-tuning and reinforcement learning executions on the Tinker platform.
Share accumulated insights via formal papers, technical blog posts, and various community contributions.

Requirements

Hold a Bachelor’s degree or possess equivalent practical experience in Computer Science, Machine Learning, Physics, Mathematics, or a related field supported by strong theoretical and empirical grounding.
Demonstrate proficiency in Python alongside familiarity with deep learning frameworks such as PyTorch or TensorFlow.
Display comfort when debugging distributed training tasks and writing scalable code.
Maintain clear communication skills with the capability to articulate intricate technical concepts through writing.
Exhibit a strong interest in the corporate mission focused on enabling custom model creation.

Nice to Have

Possess a strong comprehension of probability, statistics, and machine learning fundamentals to accurately separate real empirical effects from noise and bugs.
Bring prior hands-on experience involving RLHF, RLAIF, preference modeling, or reward learning for large models.
Have practical experience managing or analyzing human data collection campaigns and large-scale annotation workflows.
Show previous research or engineering contributions concentrated in alignment, data-centric artificial intelligence, or human-AI collaboration.
Demonstrate familiarity with reinforcement learning training stability techniques utilized during large-scale runs.
Hold a PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline, or possess equivalent industry research experience.

Skills and Tools

Python
PyTorch
TensorFlow
Distributed Training Frameworks
Parameter-Efficient Fine-Tuning (LoRA)
Reinforcement Learning Science

Salary and Benefits

Expected annual salary range spans from $350,000 to $475,000 USD, determined by background, skills, and experience.
Visa sponsorship is available for qualified candidates.
Generous health, dental, and vision benefit offerings.
Unlimited paid time off (PTO).
Paid parental leave.
Relocation support provided as needed.

About the Company

Thinking Machines focuses on a mission to build artificial intelligence that extends human will and judgment. The organization is currently training frontier models with Inkling, developing Tinker to empower individuals to make models their own, and crafting interfaces designed to broaden human-AI communication.

How to Apply

Interested candidates should visit the official Thinking Machines careers page to submit their application for this position.

Skills and tech stack

PythonPyTorchTensorFlowJAXDeep LearningMachine LearningFine-tuning

Questions candidates ask

What is the location of the Research, Finetuning Science role?

The role is based in San Francisco, California, with remote options available.

What is the salary range for this position?

The expected annual salary range is $350,000 to $475,000 USD, depending on background, skills, and experience.

Does Thinking Machines offer visa sponsorship?

Yes, visa sponsorship is provided for qualified candidates selected for the role.

What technical skills are required?

Candidates must be proficient in Python, familiar with deep learning frameworks like PyTorch or TensorFlow, and comfortable debugging distributed training.

What benefits are included?

Benefits include health, dental, and vision coverage, unlimited PTO, paid parental leave, and relocation support.

Ready to apply?

The application is on the official Thinking Machines careers page.

Apply on company site