VLM researcher

About Linewise

Linewise captures how physical things are made, from the first design to the final assembly, and turns it into training data for frontier AI and robotics models. Our long-term aim is Physical RSI: recursive self-improvement for the physical world, where AI helps engineers design and plan, robots help build and inspect, and each generation makes better machines, lines and factories for the next. This role is part of Linewise Research, which develops our methods for capture, quality control, annotation and model evaluation, and our agent-native data infrastructure. All of it is built around real industrial tasks.

About the role

You'll research how well vision-language models understand real industrial work, and how to make them better at it. You'll build benchmarks and evaluations from the kinds of data we capture, study where today's models fall short, and train models that do better. Your work shapes how we evaluate models and build datasets, and you'll have room to publish.

What you'll do

• Build benchmarks and evaluations for industrial tasks from the video and engineering data we capture.
• Evaluate open and frontier VLMs, and find out where and why they fall short.
• Train and fine-tune models on our data, and measure what improves on real tasks.
• Help set how we measure data and model quality across Linewise Research.
• Publish what you find as papers and benchmarks.

What we're looking for

• Research experience with vision-language or multimodal models, shown in papers, open-source work or models you've shipped.
• Strong Python and PyTorch, and hands-on experience training or fine-tuning large models.
• Experience designing evaluations or benchmarks.
• Comfort working with large video and image datasets.
• Clear written English. You can explain a result in a short write-up.

How we work

• You own your area end to end, from the first spec to the final delivery.
• You work closely with engineers, operators and researchers.
• English is the working language. We're based in San Francisco, with global operations.

How to apply

Send us two things:

• A short note on what you've built and what you'd like to own at Linewise.
• Your CV, or a link to your work.

Email them to info@linewise.io with the role title as the subject. The Apply button sets this up for you.