Key Responsibilities Build and ship AI features end-to-end (model → system → user experience) Design and iterate on prompts, tools, memory, and agent workflows Turn raw model outputs into structured, reliable, and predictable behaviors Debug issues across the full stack (model, orchestration, infra, UX) Optimize for latency, cost, and production reliability Develop lightweight evaluation frameworks to measure real-world performance Work closely with product and engineering to translate ambiguous problems into working systems
Tech Stack Python PyTorch / JAX LLMs (OpenAI-style APIs, LLaMA, Qwen, etc.) Inference/serving (e.g. vLLM) Vector DB
Ideal Experience Strong foundation in machine learning and modern neural network architectures. Hands-on experience with training, fine-tuning, or deploying ML models Ability to write clean, production-quality code Comfort working across abstraction layers (model → infra → product) Strong problem-solving skills in ambiguous, fast-moving environm...