Senior AI/ML Engineer – Databricks & Generative AI

About the role

We are looking for a Senior AI/ML Engineer to design, build, and productionize advanced machine‑learning and generative‑AI pipelines. You will work directly with clients and technical stakeholders to turn AI use cases into reliable, scalable solutions.

Key responsibilities

• Develop and productionize ML and GenAI pipelines on Databricks using MLflow, including feature engineering, model training, deployment, and serving.
• Build and support Generative AI and agentic AI solutions such as RAG pipelines, vector search, LLM orchestration (LangChain/LangGraph), and Databricks AI/BI tools.
• Take AI projects from data preparation and experimentation through to production deployment, creating reusable templates for RAG, assistants, forecasting, personalization, and recommendation systems.
• Optimize Databricks jobs, clusters, and workflows for performance, scalability, cost, and reliability.
• Collaborate with clients to understand requirements, resolve technical challenges, and deliver documented solutions with deployment guides and runbooks.

Required profile

• 3+ years of experience as an ML Engineer, AI Engineer, Data Scientist, or similar role with hands‑on Databricks experience.
• Proven ability to deliver production‑grade Spark applications and large‑scale ML solutions such as recommendation systems, ranking, forecasting, or personalization.
• Experience implementing Generative AI or agentic AI solutions, including RAG and LLM orchestration frameworks.
• Strong knowledge of machine‑learning fundamentals and data‑science tools.

Required skills

• Python
• PySpark
• Databricks platform
• MLflow (or similar experiment‑tracking tools)
• LangChain / LangGraph
• Pandas, scikit‑learn, PyTorch
• SQL
• Cloud platforms: AWS, Azure, GCP