Applied AI Engineer

The shape of it

In the posting’s own words

As 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.

What it asks for · 3

• 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.

Tools and skills named

Words the posting leans on

• engineers9×
• models5×
• engineering4×
• infrastructure4×
• production4×
• software4×
• systems4×
• agentic3×
• build3×
• experience3×
• machine learning3×
• solutions3×
• training3×
• agent2×
• ai/ml2×
• applied2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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