Senior ML & AI Technical Solutions Engineer

About the role

As a Senior ML & AI Technical Solutions Engineer you will help Databricks customers debug, optimise and maintain stable GenAI and ML workloads on the Databricks Platform. You will act as a technical expert across a wide range of AI agent systems, including Agent Bricks, Vector Search and Model Serving, while collaborating with engineering and account teams.

Key responsibilities

• Analyse and troubleshoot production data and ML pipelines at the code level, improving performance, reliability, latency and cost.
• Diagnose and support real‑time and batch inference for large language model deployments, including autoscaling, monitoring and alerting.
• Guide customers on experiment tracking, model registry, versioning, evaluation, labeling and lifecycle observability.
• Provide expertise on generative AI use cases such as LLMs, RAG, vector embeddings, semantic search and prompt engineering.
• Collaborate with internal teams to influence product roadmap and contribute to technical documentation.

Required profile

• 8+ years designing, building and scaling data, machine‑learning and AI systems in production.
• Strong background in Python, Scala or Java and experience with cloud platforms (AWS, Azure or GCP).
• Bachelor’s or Master’s degree in Computer Science, Engineering or related field (or equivalent experience).
• Prior experience in data‑science, ML‑engineer or AI‑engineer roles is highly valued.

Required skills

• Python, Scala, Java
• Apache Spark, data engineering pipelines
• Machine‑learning frameworks, deep‑learning, NLP
• Large Language Model (LLM) development, LangChain, LangGraph
• Vector embeddings, semantic search, Vector Search, Lakebase
• MLOps, LLMOps, model serving, model monitoring, drift detection
• Cloud platforms: AWS, Azure, GCP