Research Engineer
Hybrid (San Francisco, CA)Full-timePosted 5mo ago
About the role
AI research center for retrieval
Responsibilities
- Train models with GRPO
- Design and iterate RL training environments for retrieval – unstructured, structured, web.
- Own the entire training pipeline: from training data curation to wandb.
- Run small and large model experiments – yolo runs encouraged.
- Work on next-generation vision-first embedding models.
- Lead discussions on research – reading group.
- Work directly with the ex-research CEO.
- Future: Manage a team of research engineers.
Qualifications
- Not afraid of formulas – a BSc/MSc/PhD is an indicator of this (but isn't the only one).
- Thinks they can learn anything in 2 weeks, but isn't arrogant about it.
- Prefers .py to .tex
- Familiar with vLLM/SkyRL/Megatron/etc.
- Comfortable with torchrun/accelerate/multi-node training.
- Clever about getting the data needed – or synthetically generating it.
- Finds easy solutions to hard problems, but doesn't mind getting their hands dirty with PyTorch or CUDA.
- Publications are a plus, but being able to critically evaluate research is a must.
- Familiar with 'You and Your Research.' Understands what it takes to do significant work.
- Must articulate ideas well! A big part of making successful models is telling people about them. This includes writing docs and technical reports at the minimum – and jumping on podcasts at the extreme.
Skills
Required:Torch/PyTorchReinforcement learning (RL)CUDASearchLLMsVector Embeddings
Nice to have:AI AgentsMLOps
Benefits
- Non-bureaucratic compute approvals: If you want to train a model, you can. We've budgeted 100,000 H100 hours for this role. If things go well, this number will be higher.
- Work on frontier methods that scale. No weird old-school AI.
- Everyone on the team can code – this might change in the future of course.
- Competitive compensation with generous early-stage equity, full medical and vision.
Last updated Oct 7, 2026. Interested? Apply on the company site.
About SID
Serverless RAG to connect AI to company, industry, or person-specific…
We make it easy for developers to connect data to their LLM apps. Instead of spending months on integrations and retrieval pipelines, Reworkd's AgentGPT added our button in an afternoon and let thousands of people connect their Notion, email and Drive instantly. Every single AI company is building data retrieval. Currently, they're doing this from scratch – we don't think they should have to. Just like OpenAI made working with LLMs as simple as an API call, SID makes it easy for every AI company to access data the same way.
More open roles at SID
- Research Intern (Summer 2026)11mo agoSan Francisco, CA