Senior Applied ML Engineer - ML4Sys

What this role involves

This is a Senior Applied ML Engineer role on the Applied AI team at Databricks, focusing on ML4Sys (machine learning for systems). The role involves using ML, scheduling, and optimization to improve infrastructure efficiency and performance, spanning from cluster management to query compilation. Responsibilities include building end-to-end ML4Sys solutions, defining strategy, deploying models, and scaling infrastructure. Minimum qualifications include a Master's degree in a related field, strong ML production experience, and proficiency in Python, Scala, or Java. Preferred qualifications include a PhD, 4+ years of ML engineering experience, and expertise in systems and optimization.

Skills this posting asks for

• machine learning
• scheduling
• optimization
• python
• scala
• java
• cloud computing
• distributed systems
• data processing frameworks
• computer architecture
• distributed computing
• database internals
• networking
• operations research
• forecasting
• markov decision processes
• ml pipelines
• model serving
• production monitoring

Requirements

• Level: senior

From the employer’s posting

RDQ127R59 Summary As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will…