Databricks
About this role
Databricks sells the lakehouse platform a large part of the data and AI industry builds on, and this role is the machine learning specialist inside its field engineering organisation. You would be the technical ML and AI expert for both customers and Databricks' own field teams, working alongside solution architects to guide customers into production grade ML and AI on the platform. The hands on part is real: building, scaling and optimising customer AI workloads and applying MLOps practices to get them into production across different domains. The posting keeps the technical bar high, asking for 5 or more years of hands on industry ML experience as either an ML engineer running cloud infrastructure for model deployment and drift monitoring, or an AI engineer working with LLMs, agentic systems, vector databases, fine tuning and guardrails.
Who this is for
Required by the posting: 5 or more years of hands on industry ML experience in at least one of two tracks. As an ML engineer, building and maintaining production grade cloud infrastructure on AWS, Azure or GCP supporting ML application deployment, including drift monitoring. As an AI engineer, experience with current LLM and agentic system techniques including vector databases, fine tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, LangChain and OpenAI. A graduate degree in a quantitative discipline such as computer science, engineering, statistics or operations research, or equivalent practical experience. Experience communicating or teaching technical concepts to both technical and non technical audiences.
Preferred, not required: 2 or more years of customer facing experience in a pre sales or post sales role. Note the direction of that requirement, since it means deep ML skill with limited customer facing time is acceptable, but the reverse is not.
The day to day: act as the trusted technical ML and AI expert to Databricks customers and to the field engineering organisation. Work with solution architects to guide customers in architecting production grade ML and AI applications on Databricks. Build, scale and optimise customer AI workloads and apply MLOps to productionise them across a variety of domains.
Location: the posting states plainly that this is a hybrid role based in Bengaluru. The hiring entity is Databricks India Private Limited and the posting category is Field Engineering.
Who should apply: ML and AI engineers five or more years in who enjoy customer work. It is a customer facing seat, so travel and meetings replace some build time, but the technical requirement is hands on rather than presentational.
Preferred, not required: 2 or more years of customer facing experience in a pre sales or post sales role. Note the direction of that requirement, since it means deep ML skill with limited customer facing time is acceptable, but the reverse is not.
The day to day: act as the trusted technical ML and AI expert to Databricks customers and to the field engineering organisation. Work with solution architects to guide customers in architecting production grade ML and AI applications on Databricks. Build, scale and optimise customer AI workloads and apply MLOps to productionise them across a variety of domains.
Location: the posting states plainly that this is a hybrid role based in Bengaluru. The hiring entity is Databricks India Private Limited and the posting category is Field Engineering.
Who should apply: ML and AI engineers five or more years in who enjoy customer work. It is a customer facing seat, so travel and meetings replace some build time, but the technical requirement is hands on rather than presentational.
Apply on company site
Opens databricks.com, the employer's own application page. Applying is always free.