About the role
Software should be beautiful.
Variant is code generation with creativity and taste. Instead of a confined conversation, you can generate endless designs from a single idea. Freely explore, discover directions you wouldn’t have thought of, and build better software as a result.
We're well-capitalized and looking for an applied researcher to join us at Variant.
Job Responsibilities:
- Design, train, and evaluate deep neural networks and LLMs
- Own experiments end-to-end: hypotheses, datasets, metrics, results
- Prototype fast; turn promising ideas into reliable systems
- Collaborate with engineering and design to make ideas real
- Write clearly: papers, docs, and crisp experiment reports
- Don't compromise between rigor and shipping fast
- See what needs to be done and do it
Minimal qualifications:
- 2+ years in PhD program or in industry
- Experience training deep neural networks
- Proficiency in frameworks like Pytorch
- Published 1 or more papers in the subject of deep learning
Ideal qualifications:
- Experience training LLMs, including SFT, RL-based techniques, etc.
- Experience in the domain of code generation
- At least 1 paper accepted into a top conference
- Proficiency in best software engineering practices
- Repeated experience formulating, structuring, and answering open ended questions
- Passionate about visual design or UI design; prior work in the space
We've kept our team small by design. Your code will matter from day one, and its impact will compound over time. . We work from a beautiful space in San Francisco where we dream up the future and make it real together. We’re well-capitalized and backed by notable investors. If you've built things you're proud of, we'd love to see them.
