Senior ML & AI Technical Solutions Engineer
Databricks
Bengaluru, IndiaPosted 1 month ago
Skill Required
SupportMachine Learning EngineerAI EngineerTechnical LeadAIMachine LearningSystem DesignGenerative AIDeep Learningrelated fieldObservabilityEngineeringDatabricksData StructuresLangChaindesigningdebuggingbuildingPythondesignScalaSparkAzureUnityCloudJavaAPIsNLPRAG
Key highlights
- 8+ years of required experience.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
- Comprehensive benefits and perks.
- Familiarity with Databricks is a plus.
- Experience with cloud platforms (AWS, Azure, or GCP).
- Prior experience in Data Scientist, ML Engineer, or AI Engineer roles is highly valued.
Role overview
As a Senior ML and AI Technical Solutions Engineer, you play a critical role by helping customers debug and maintain stable GenAI and ML Workloads with AI agent systems using the Databricks Platform. You will 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 will 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. TSEs have proven production troubleshooting and optimisation experience to help our customers’ workloads run smoothly and to achieve their strategic objectives with ML/AI technology with Databricks. Additionally, you are an early adopter of GenAI technology to improve your own efficiency and amplify the team's output.
Responsibilities
- Help customers debug and maintain stable GenAI and ML Workloads with AI agent systems using the Databricks Platform.
- 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.
- 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.
- Act as senior technical solution expert for complex issues spanning data pipelines, ML pipelines and/or AI applications, applying deep expertise in distributed systems.
- Analyse and troubleshoot production workloads at the code level, optimise 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, labelling, tracing, and lifecycle observability.
- Provide high‑quality support by guiding customers in leveraging Databricks AI to solve generative AI use cases & 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 your knowledge by contributing to wikis and other technical documentation, or by teaching our AI systems new skills, which will be used internally and externally by customers and partners.
- Report to a TSE manager and be part of a world‑class global support engineering organization for Databricks, known for your technical depth and delivering impeccable customer service.
- Early adopter of GenAI technology to improve your own efficiency and amplify the team's output.
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 environments, with expertise in Machine Learning and/or generative AI.
- Experience with cloud platforms (AWS, Azure, or GCP).
- SME knowledge in feature engineering, ML frameworks, model training, model monitoring, drift detection, and retraining strategies.
- Proficient in data engineering necessary for orchestrating end‑to‑end machine learning training pipelines, ideally with experience processing large datasets with Apache Spark.
- 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 etc).
- 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, optimisation, training, validation, and packaging.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
- Ability and desire to develop excellent customer service skills.
Nice to have
- Familiarity with Databricks is a plus.
- Experience developing agent skills, plugins, and debugging with native AI capabilities.
- Professional certifications are good to have.
- Prior support or customer‑facing experience is not required for this role, but the ability and desire to develop excellent customer service skills are.
- Prior experience in Data Scientist, ML Engineer, or AI Engineer roles is highly valued.
Benefits
- Comprehensive benefits and perks that meet the needs of all employees (specific details vary by region).
- Access to a diverse and inclusive culture with equal employment opportunity standards.
Additional details
- P-1377
- 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 70% of the Fortune 500 — rely on the Databricks Data + AI Platform 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 platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog.
- Compliance: If access to export‑controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
- Our Commitment to Diversity and Inclusion: At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards.