- Design, build, and deploy production ML and LLM-based systems (RAG, agentic workflows, fine-tuning, embeddings) for enterprise clients
- Own technical delivery end-to-end: from architecture and prototyping to deployment, monitoring, and iteration
- Work directly with client engineering and product teams to translate business needs into scoped, shippable technical solutions
- Mentor and support other ML engineers on the team through code reviews, technical guidance, and knowledge sharing
- Help shape internal best practices, tooling, and technical standards as the team grows
- Represent TensorOps technically in client conversations, workshops, and optionally at industry conferences
PythonMachine LearningPyTorch+6 more