Staff Machine Learning Engineer

<p>P-1504</p> <p>The Applied AI team at Databricks sits at the forefront of advancing GenAI-powered products. Over the past years, we’ve launched&nbsp;<a class="c-link" href="https://www.databricks.com/blog/introducing-databricks-assistant" target="_blank" data-stringify-link="https://www.databricks.com/blog/introducing-databricks-assistant" data-sk="tooltip_parent">Databricks Assistant</a>,&nbsp;<a class="c-link" href="https://www.databricks.com/product/ai-bi/genie" target="_blank" data-stringify-link="https://www.databricks.com/product/ai-bi/genie" data-sk="tooltip_parent">AI/BI Genie</a>, and&nbsp;<a class="c-link" href="https://www.databricks.com/blog/introducing-agent-bricks" target="_blank" data-stringify-link="https://www.databricks.com/blog/introducing-agent-bricks" data-sk="tooltip_parent">Agent Bricks&nbsp;</a>working with product teams, and made significant strides in LLM quality for these products. These products are used by 100s of thousands of Databricks users every day. We are tackling challenging problems like code suggestion, error detection and correction, text-to-sql generation, automatic pipeline generation, knowledge QA and many others.</p> <p>As our GenAI products continue to evolve, we are seeking multiple <strong>&nbsp;GenAI Engineers from junior levels to more senior levels</strong> to drive the next phase of development. In 2025, we will focus on enhancing LLM quality, expanding GenAI capabilities across Databricks products, and strengthening our platform architecture to enable seamless AI interactions at scale.</p> <p><strong>Key Responsibilities</strong></p> <ul> <li>Shape the direction of our applied AI areas and intelligence features in our products<strong>. </strong>Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services (e.g., Databricks Assistant and AI/BI Genie).</li> <li>Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains.</li> <li>Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration.</li> <li>Work closely with cross-functional teams, including AI researchers, ML engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction.</li> <li>Build scalable, reusable backend systems to support GenAI products across the company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable mod