Research Engineer, Visual Knowledge Work

About the role

We're looking for a research engineer who believes that visual and spatial reasoning are core to fully unlocking the capabilities of LLMs. On the Vision team, you'll own the end-to-end process of creating training data and RL environments targeting visual knowledge work: identifying long-horizon and vision-heavy tasks, building evals, designing rewards, and scaling data. This role combines applied research with hands-on data work and is highly collaborative.

What you'll do

• Own the data strategy for vision capabilities end-to-end, from building evals and scaling RL environments
• Manage technical relationships with external data vendors, including writing task specifications, evaluating visual data and annotation quality, and iterating on reward design
• Develop and improve QA frameworks that catch reward hacking and ensure environment quality at scale
• Run generalization experiments to measure how data strategy changes improve multimodal capabilities on held-out evaluations
• Partner with pretraining, RL, and product teams, and conduct the science that aligns team efforts

Qualifications

• 7+ years of ML, computer vision, and software engineering experience through industry, academia, or other projects
• Experience with reinforcement learning, reward design, or training data curation for large language or vision-language models
• Familiarity with the architecture, training, and operation of large vision language models
• Comfortable managing technical vendor relationships and iterating quickly on feedback
• Results-oriented, with a bias towards flexibility and impact
• Care about the societal impacts of your work

Nice to have

• Experience designing evals or benchmarks for LLMs or vision language models
• Experience with large-scale pretraining, SL, and RL on language models
• Deep learning research on images, video, or other modalities
• Experience developing complex agentic systems using LLMs
• Large-scale ETL and data pipeline development experience

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Hybrid policy: Currently, all staff are expected to be in one of our offices at least 25% of the time, though some roles may require more office presence.
• Visa sponsorship: Visa sponsorship is available for qualified candidates.