Lead end-to-end ML implementations for clients, design and maintain production-grade MLOps pipelines, deploy and optimize Generative AI/LLM and NLP solutions, manage infrastructure (Docker, orchestration, distributed compute), and communicate technical results to stakeholders.

Design and maintain robust CI/CD pipelines, manage integrations with large customer repositories, develop full-stack software, provision cloud infra with Terraform, and implement scalable data pipelines. Learn and apply PySpark, modern data architecture, and AI/agentic tools (Claude, Cursor) to automate and accelerate engineering workflows.