Staff Machine Learning EngineerActive$190K

Databricks
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The opportunity

The Applied AI team at Databricks sits at the forefront of advancing GenAI-powered products. Over the past years, we’ve launched Databricks Assistant , AI/BI Genie , and Agent Bricks working with product teams, and made significant strides in LLM quality for these products.

What you'll do

  • Shape the direction of our applied AI areas and intelligence features in our: products . 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).

  • Develop novel data collection, fine-tuning, and LLM technologies that achieve: optimal performance on specific tasks and domains.

  • Design and implement ML pipelines for data preprocessing, feature: engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration.

  • 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.

  • Build scalable, reusable backend systems to support GenAI products across the: company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable model performance.

  • years of machine learning engineering experience in high-velocity,: high-growth companies. Alternatively, a strong background in relevant ML research in academia will be considered as an equivalent qualification.

What they're looking for

  • Strong track record of working with language modeling technologies. This: could include the following: Developing generative and embedding techniques, modern model architectures, fine tuning / pre-training datasets, and evaluation benchmarks.
  • Proficiency in Python, TensorFlow/PyTorch, and scalable ML architectures.
  • Ability to drive end-to-end model development, from research and prototyping to deployment and monitoring.
  • Strong analytical and problem-solving skills, with a passion for improving AI-driven user experiences.