About the Role :

We are a San Francisco-based AI infrastructure company working with leading frontier AI labs to build post-training data and evaluation infrastructure for foundation models. We are hiring a Python Developer to create high-quality datasets, reinforcement learning environments, and benchmarking pipelines used to improve and evaluate state-of-the-art LLMs. This is a remote role with flexible working hours.

Responsibilities :

- Create and curate datasets for LLM post-training (SFT, RLHF, RL, preference optimization).

- Build and maintain RL environments for agent evaluation.

- Develop Python tooling for dataset generation, validation, and transformation.

- Evaluate models on custom benchmarks and testing pipelines.

- Collaborate with research and engineering teams to deliver client-specific post-training datasets.

- Work with terminal-first development workflows and cloud infrastructure.

Required Skills :

- Strong Python programming skills.

- Understanding of LLM fundamentals and post-training concepts (SFT, RLHF, RL).

- Experience working with structured data (JSON, CSV, YAML).

- Git, Linux/Unix command line, and solid software engineering fundamentals.

Good to Have :

- Experience with RAG, agentic AI systems, Hugging Face Transformers, LoRA/PEFT, LangChain or LlamaIndex, vector databases (FAISS, Qdrant, Milvus, Pinecone, Weaviate, ChromaDB), Docker, AWS/GCP, FastAPI/Flask, Bash, CLI tooling, model evaluation frameworks, benchmarking, and AI infrastructure.

Compensation :

- Base Salary : USD $1,250/month

- Equity : ESOP/Equity package included.

- Performance Bonuses : Up to USD $4,000/month (in addition to base salary).