We’re building next-generation AI products powered by large language models — and we’re looking for an experienced Machine Learning Engineer who knows how to bring cutting-edge research to life in production.

What you’ll do

• Design, build, and optimize AI pipelines using OpenAI, OpenRouter, and other model APIs
• Develop and refine architectures such as RAG, ReAct, and multi-agent systems
• Integrate and orchestrate workflows with LangChain, LangGraph, or LlamaIndex
• Prepare, clean, and structure datasets for training and fine-tuning
• Fine-tune and evaluate transformer-based models with PyTorch and Hugging Face
• Implement and optimize quantization, inference acceleration, and LLM ops (e.g. vLLM, DeepSpeed, bitsandbytes)
• Experiment with embeddings, retrieval, and routing strategies to improve model quality and latency
• Collaborate closely with backend and product teams to deliver scalable, real-world AI features

What we’re looking for

• Strong practical experience with LLM APIs (OpenAI, OpenRouter, Anthropic, etc.)
• Solid knowledge of LangChain and agentic architectures (RAG, ReAct, Tool use)
• Hands-on experience with PyTorch, Hugging Face Transformers, and fine-tuning pipelines
• Understanding of quantization, inference optimization, and vLLM
• Experience with vector databases (FAISS, Qdrant, Pinecone)
• Strong Python skills (FastAPI, Pydantic, etc.)

Nice to have

• Knowledge of graph-based memory systems or retrieval pipelines
• Familiarity with LangGraph, LlamaIndex, or multi-agent orchestration
• Experience deploying models to production (Docker, Kubernetes, AWS/GCP)

We offer

• Work on real AI products used by thousands of people
• Autonomy, fast iteration, and visible impact
• Remote-first team, flexible hours, and a culture of curiosity and creativity