Machine Learning Engineer

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI.

• 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.

• 2-8 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.
• 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.
• 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.

• Pay range: $190,000 — $285,000 USD.