Senior Applied AI Engineer

P-1439

As a Senior Applied ML/AI Engineer at Databricks, you will define and create the Agentic Machine Learning revolution. You will help world’s largest companies build and deploy massive classical machine learning solutions (such as personalized recommendations, fraud detection, dynamic pricing, forecasting) fully using Databricks’ agents and harnesses. After 30 years of painfully slow progress, expensive knowledge acquisition and tedious processes in classical ML, the agentic era has ushered innovation, scale and visibility for all: from the most junior data scientists and machine learning engineers to the world class experts. You will work on Databricks’ Genie Code, an agent and an ML “exoskeleton” that is authoring ML, training and deploying models, monitoring and self-healing production ML, all at the top-expert level. Additionally, you will develop ML solutions that under the hood address the most pressing questions non-technical business people have today: predictive and what-if questions.

Your work is a top priority for Databricks and you will report to a Principal Software Engineer (a Director level position).

The impact you will have:

• Build agentic end-to-end systems in a small, highly international team of experienced engineers in a flat and agile organization.
• Build solutions for people like you: software engineers, ML engineers, data engineers, data scientists and MLOps engineers.
• Own our applied ML investment by engaging with engineering and product teams across the company.
• Drive 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.
• Architect and implement robust, scalable ML infrastructure, including model training and serving components to support seamless integration of AI/ML models into production environments.
• Work on novel forecasting techniques.
• Possibilities to contribute to the broader AI community by presenting at conferences and actively participating in open source projects, enhancing Databricks’ reputation as an industry leader.

What we look for:

• 2-8 years of engineering experience in high-velocity, high-growth companies. Infrastructure and system engineers with no ML background and willingness to excel in personal growth are welcome to apply.
• Strong software engineering skills, and familiarity with software engineering principles around testing and deployment.
• Experience developing AI/ML systems at scale in production and a strong track record of ML modeling that goes beyond using standard libraries is a plus.
• Nice to have: experience deploying, scaling, and monitoring models in production; understanding of the unique infrastructure challenges posed by training and serving predictions in Tier 0 environments.