AI Engineer

We are hiring interns who are strong in any one of these four areas. You do not need all four. Pick your strongest layer and apply.

Responsibilities:

• Build and ship working systems, not slide decks.
• Own your work end-to-end: design, build, benchmark, document.
• Work directly with the founders and senior engineers.
• Go deep in your layer while getting exposure to the other three.

Requirements:

• Proof of good work in your chosen area. That could be:
• A project you built and can demo.
• Open-source contributions.
• Kaggle, GSoC, hackathons, or a solid technical write-up.

Expected skills in any one field:

• LLMOps: serving open-weight models with vLLM or SGLang, GPU infrastructure, quantization, Kubernetes deployment, latency, and cost benchmarking.
• Enterprise RAG: ingestion and chunking pipelines, embeddings, hybrid retrieval and reranking, and retrieval quality evals.
• Model fine-tuning: dataset curation, LoRA/QLoRA and full fine-tunes, instruction tuning, and eval design.
• AI agents and workflows: multi-step agents, tool use, orchestration, memory, guardrails, and workflow automation.