Research, Vision Expertise

Thinking Machines Lab Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 350,000 - 475,000; Full time

Benefits offered by this job

Health benefits

Dental benefits

Vision benefits

Unlimited PTO

Parental leave

Relocation support

Job summary

Thinking Machines Lab Inc. in San Francisco, CA is seeking a researcher to advance multimodal AI at scale, blending vision and language. You will design experiments, build datasets, and contribute to training large-scale models that ground concepts in the physical world.

The role blends research and engineering, requiring writing high-performance code, reading technical reports, and publishing results. A PhD or equivalent industry experience in ML or related fields is preferred.

Qualifications

• Design, run, and analyze experiments with empirical rigor.
• Strong understanding of ML fundamentals and distributed compute.
• Proficiency in Python and at least one DL framework; scalable code.
• Bachelor’s degree or higher in CS/ML/Physics/Math with strong grounding.
• Excellent written communication.

Responsibilities

• Own research projects on training and performance analysis of multimodal AI models.
• Curate and build large-scale datasets and benchmarks.
• Collaborate with data infra engineers, researchers, and product teams.
• Publish research and share code, datasets, and insights with the community.

Job description

The mission of Thinking Machines is to build AI that extends human will and judgment.

About the Role

Thinking Machines builds multimodal-first.We’re looking for new team members to advance the science of visual perception and multimodal learning. We think about how vision and language interact at scale. We design architectures that fuse pixels and text, build datasets and evaluation methods that test real-world comprehension, and develop representations that let models ground abstract concepts in the physical world. Our goal is to create multimodal systems that support seamless integration into real-world environments.

You’ll work at the intersection of visual understanding, multimodal reasoning, and large-scale model training. You’ll help develop the architectures, data, and evaluation tools that teach AI to see, understand, and collaborate. The best candidate is curious about multimodal interfaces, has experience running large scale experiments and is comfortable contributing to complex engineering systems. While we are looking for a person with expertise in multimodality, Thinking Machines Lab operates in a unified fashion and expects new hires to work across modalities as one team.

This role blends fundamental research and practical engineering, as we do not distinguish between the two roles internally. You will be expected to write high-performance code and read technical reports. It’s an excellent fit for someone who enjoys both deep theoretical exploration and hands‑on experimentation, and who wants to shape the foundations of how AI learns.

What You’ll Do

• Own research projects on training and performance analysis of multimodal AI models.

• Curate and build large-scale datasets and evaluation benchmarks to advance vision capabilities.

• Work with our data infrastructure engineers, pretraining researchers and engineers, and product team to create frontier multimodal models and the products that leverage them.

• Publish and present research that moves the entire community forward. Share code, datasets, and insights that accelerate progress across industry and academia.

Skills and Qualifications

Minimum qualifications:

• Ability to design, run, and analyze experiments thoughtfully, with demonstrated research judgment and empirical rigor.

• Understanding of machine learning fundamentals, large-scale training, and distributed compute environments.

• 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.

Preferred qualifications — we encourage you to apply even if you don’t meet all preferred qualifications, but at least some:

• Research or engineering contributions in visual reasoning, spatial understanding, or multimodal architecture design.

• Experience developing evaluation frameworks for multimodal tasks.

• Publications or open-source contributions in vision‑language modeling, video understanding, or multimodal AI.

• A strong grasp of probability, statistics, and ML fundamentals. You can look at experimental data and distinguish between real effects, noise, and bugs.

• PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience.

Logistics

• Location: This role is based in San Francisco, California.

• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.

• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.

• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.