Applied Researcher

• 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. This will be the most meaningful work of your career.
• 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.