Description:

Own the architecture and delivery of production-grade LLM systems and classical ML solutions.
Design, evaluate, and optimize RAG pipelines and build scalable LLM services.
Define architecture trade-offs with a focus on system-level optimization.
Architect and optimize distributed GenAI and ML workloads on Databricks.
Implement evaluation frameworks and productionize systems with CI/CD.
Independently design AI solutions tailored to client problems and mentor team members.

Requirements:

5+ years of experience in Data Science or a related field.
Proven experience delivering LLM-based systems to production and classical ML projects.
Strong hands-on experience with RAG, agents, and open-source LLMs.
Deep understanding of system-level trade-offs and experience optimizing production systems.
Strong Python and SQL skills, and experience with Databricks and distributed computing.
Experience deploying scalable ML/LLM systems on AWS, Azure, or GCP.
Client-facing experience and clear communication in English.

Skills

Benefits