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What is it like to work at Databricks?

Databricks is known for its collaborative and innovative culture, prioritizing teamwork, open communication, and continuous learning. The company's structure is designed to foster a sense of community, with cross-functional teams working together to drive product development and customer success, often in an open and modern office environment. Working at Databricks may appeal to candidates who are passionate about data and AI, as the company offers opportunities to work on cutting-edge projects, collaborate with industry experts, and contribute to the growth of a rapidly expanding field.
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Infographic showing various Machine Learning Engineer job openings at Databricks in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 92% Physical, and 8% Remote job distribution.

Staff Machine Learning Engineer

Databricks

San Francisco, CA • On-site

Full-time

Re-posted 25 days ago

Job description

Job Summary:
Databricks is a leading data and AI company that focuses on advancing GenAI-powered products. The Staff Machine Learning Engineer will shape the direction of applied AI features, develop state-of-the-art AI models, and collaborate with cross-functional teams to enhance user productivity and satisfaction.
Responsibilities:
• 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.
Qualifications:
Required:
• 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.
Preferred:
• Experience with LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) is a bonus.
Company:
Databricks is a data and AI platform that unifies data engineering, analytics, and machine learning on a lakehouse architecture. Founded in 2013, the company is headquartered in San Francisco, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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