Staff Machine Learning Engineer

2-8 years of machine learning engineering experience in high-velocity, high-growth companies.

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 coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment.

Experience with LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) is a bonus.

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.