Senior ML & AI Technical Solutions Engineer

P-1377

Mission

As a Senior ML and AI Technical Solutions Engineer, you help customers debug and maintain stable GenAI and ML workloads with AI agent systems using the Databricks Platform. You develop product expertise end-to-end by advising a broad set of customers and use cases across the space, including products such as Agent Bricks, Vector Search and Model Serving. You collaborate cross-functionally with other teams—whether that’s working with engineering to improve the product or interacting directly with the account team on a specific customer issue.

You have proven production troubleshooting and optimization experience to help customers’ workloads run smoothly and achieve their ML/AI objectives with Databricks. You are an early adopter of GenAI technology to improve your own efficiency and amplify the team’s output. You report to a TSE manager and are part of a global support engineering organization known for technical depth and impeccable customer service."

The Impact You Will Have

• Act as a senior technical solution expert for complex issues spanning data pipelines, ML pipelines and/or AI applications, applying deep expertise in distributed systems.
• Analyze and troubleshoot production workloads at the code level, optimizing for performance, reliability, latency, and cost.
• Diagnose and support Machine Learning and/or Large Language Model deployments, including real-time and batch inference, autoscaling, monitoring, logging, and alerting. Serve as a Subject Matter Expert guiding customers on experiment tracking, model registry, versioning, evaluation, labeling, tracing, and lifecycle observability.
• Provide high-quality support by guiding customers in leveraging Databricks AI to solve generative AI use cases and challenges, leveraging LLMs, MCP, AI Agents, RAG/Agentic RAG, APIs, vector embeddings, semantic search, Vector Search/Lakebase databases, context orchestration, memory management, and prompt engineering.
• Collaborate with internal teams to influence roadmap, product improvements and support business growth.
• Develop expertise in productionizing systems in Databricks and share knowledge by contributing to wikis and other technical documentation, or by teaching our AI systems new skills for internal and external use by customers and partners.

What We Look For

8+ years of experience designing, building, and scaling data, machine learning, and AI systems on-premises and in the cloud using Python, Scala, and Java in production environments, with expertise in ML and/or generative AI. Experience with cloud platforms (AWS, Azure, or GCP); familiarity with Databricks is a plus. Proficient in data engineering necessary for orchestrating end-to-end ML training pipelines, ideally with experience processing large datasets with Apache Spark.

• Subject-matter-expert knowledge in feature engineering, ML frameworks, model training, model monitoring, drift detection, and retraining strategies. Proficient in working with algorithms and deep learning, along with NLP techniques.
• Prior experience building, designing or troubleshooting LLM-based Generative AI applications. Familiarity with agentic frameworks (e.g., LangChain, LangGraph). Expertise in context orchestration, including prompt design, memory management, retrieval systems, vector embeddings, semantic search, and tool integrations.
• Comprehensive knowledge of MLOps and LLMOps with expertise in model evaluation, scoring, ranking, optimization, training, validation, and packaging.
• Experience developing agent skills, plugins, and debugging with native AI capabilities is a plus.
• Prior customer-facing experience is not required, but the ability and desire to develop excellent customer service skills are important.
• Prior experience in roles such as Data Scientist, ML Engineer, or AI Engineer is highly valued.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience). Professional certifications are a plus.

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.

For more information, follow Databricks on LinkedIn and other social channels.

Benefits

Databricks strives to provide comprehensive benefits and perks that meet the needs of all employees. For specific details on benefits offered in your region, please refer to the official benefits page for your location.

Our Commitment to Diversity and Inclusion

Databricks is committed to fostering a diverse and inclusive culture where everyone can excel. Our hiring practices are inclusive and comply with equal employment opportunity standards. Databricks considers applicants without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, the Employer may determine whether to apply for a U.S. government license for such positions, and may decline to proceed with an applicant on that basis alone.