Bengaluru, India
Open 6 months, first seen by us 199 days agoTroubleshoot production ML and AI workloads at the code level, optimising performance, reliability, latency and cost
Diagnose LLM and ML deployments, including real-time and batch inference, autoscaling and monitoring
Guide customers on generative AI use cases using LLMs, AI agents, RAG and vector search
Work with engineering and account teams to improve the product and resolve customer issues
Write wikis and technical documentation on productionizing systems in Databricks
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.
guiding customers in leveraging Databricks AI to solve generative AI use cases & challenges, leveraging LLMs, MCP, AI Agents, RAG/Agentic RAG
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.
contributing to wikis and other technical documentation
- Prior experience in Data Scientist, ML Engineer, or AI Engineer roles is highly valued. - Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience). Professional certifications are good to have. About Databricks
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.
In the employer’s words · Read in context
Open 6 monthsWe first saw this posting 199 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
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Day 199
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past Databricks’s usual: its jobs come down by about day 63.
From 5,460 similar postings that came down, and 19 of Databricks’s. Coming down is not always a hire.
29 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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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 Machine Learning 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 machine learning training pipelines, ideally with experience processing large datasets with Apache Spark. - SME 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.
Mission 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. Reporting to a TSE manager - you will be part of a world class global support engineering organization for Databricks, known for your technical depth and delivering impeccable customer service. The Impact You Will Have
- 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.
- 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. What We Look For
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience). Professional certifications are good to have. 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. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits
Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion
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. Individuals looking for employment at Databricks are considered 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
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
P-1377
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. Reporting to a TSE manager - you will be part of a world class global support engineering organization for Databricks, known for your technical depth and delivering impeccable customer service.
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 Machine Learning 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 machine learning training pipelines, ideally with experience processing large datasets with Apache Spark.
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. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
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. Individuals looking for employment at Databricks are considered 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, 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.
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Bengaluru, India
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