Description:

Contribute to technical direction across client engagements and mentor junior ML engineers.
Design, build, and deploy production ML and LLM-based systems for enterprise clients.
Own technical delivery from architecture to deployment and monitoring.
Work with client teams to translate business needs into technical solutions.
Shape internal best practices and represent TensorOps in client conversations.

Requirements:

2+ years of professional experience in Machine Learning or AI Engineering.
Strong skills in Python and production-quality code.
Experience in designing, training, and deploying ML models (e.g., PyTorch, TensorFlow).
Familiarity with GenAI & LLM systems and MLOps practices.
Experience deploying ML systems on AWS, GCP, or Azure.
Strong performance optimization and debugging skills.
Client interaction experience is a plus.

Skills