From statistical models all the way down to deep and foundational models, feature augmentation and auto-tuning, our Applied ML/AI team works on some of the most complex, most interesting problems facing businesses, making Databricks' infrastructure and products as performant and cost-efficient as possible.

This is a high-impact problem as our customers look at us to deliver the most out of their data.

Key responsibilities include:

• Building features and running end-to-end systems in a small team of experienced engineers and data scientists.
• Shaping the direction of our applied ML investment by engaging with engineering and product teams across the company.
• Driving the development and deployment of state-of-the-art ML/AI models and systems that directly impact the capabilities and performance of Databricks’ products, infrastructure, and services.
• Architecting and implementing robust, scalable ML infrastructure, including model training and serving components to support seamless integration of AI/ML models into production environments.
• Working on novel modeling techniques in the field of ML for forecasting.

What we look for:

• 2-8 years of machine learning engineering experience in high-velocity, high-growth companies.
• Strong understanding of both computer systems and statistics.
• Experience developing AI/ML systems at scale in production.
• Strong track record of ML modeling that goes beyond using standard libraries.
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews, and deployment.
• A large breadth of knowledge or willingness to develop mathematical modelling beyond the ML.

Why Join Us?

At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you!

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