Senior ML & AI Technical Solutions Engineer
Databricks17 days ago
Responsibilities
- Act as a senior technical expert for complex issues involving data pipelines, ML pipelines, AI applications, and distributed systems.
- Analyze and troubleshoot production workloads at the code level and optimize performance, reliability, latency, and cost.
- Diagnose and support machine learning and LLM deployments, including real-time and batch inference, autoscaling, monitoring, logging, and alerting.
- Guide customers on experiment tracking, model registries, versioning, evaluation, labeling, tracing, lifecycle observability, and Databricks AI use cases.
- Advise customers on LLMs, MCP, AI agents, RAG, agentic RAG, vector embeddings, semantic search, context orchestration, memory management, and prompt engineering.
- Collaborate with engineering and account teams to improve products, influence the roadmap, and support business growth.
- Create technical documentation, share knowledge through wikis and teaching, and contribute to internal and external AI capabilities.
Requirements
- 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.
- Expertise in machine learning and/or generative AI, with experience using AWS, Azure, or GCP; Databricks experience is a plus.
- Proficiency in data engineering for orchestrating end-to-end ML training pipelines and ideally processing large datasets with Apache Spark.
- Subject matter expertise in feature engineering, ML frameworks, model training, model monitoring, drift detection, retraining strategies, algorithms, deep learning, and NLP techniques.
- Experience building, designing, or troubleshooting LLM-based generative AI applications and familiarity with agentic frameworks such as LangChain or LangGraph.
- Expertise in context orchestration, prompt design, memory management, retrieval systems, vector embeddings, semantic search, and tool integrations.
- Comprehensive knowledge of MLOps and LLMOps, including model evaluation, scoring, ranking, optimization, training, validation, and packaging.
- Experience developing agent skills or plugins and debugging with native AI capabilities is a plus.
- Prior experience in Data Scientist, ML Engineer, or AI Engineer roles is highly valued; prior customer-facing or support experience is not required.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience; professional certifications are preferred.
Benefits
- Databricks offers comprehensive benefits and perks tailored to employees’ needs, with region-specific details available from the employer.
- The role is part of a global support engineering organization and may involve access to export-controlled technology subject to employer discretion and government licensing.
Tech Stack
Categories
Solutions Engineering
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and over 60% of the Fortune 500 — rely on Databricks to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified Data Intelligence Platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase and Unity Catalog. --- Databricks applicants Please apply through our official Careers page at databricks.com/company/careers. All official communication from Databricks will come from email addresses ending with @databricks.com or @goodtime.io (our meeting tool).