Machine Learning Engineer With Google Cloud Platform

Data & Machine Learning Engineer 

Job Details

 *Skills
Google Cloud
Google Cloud Platform
Java
Machine Learning (ML)
Systems Modeling
Streaming
Debugging* 

Summary
Introduction: The System Engineer will be responsible for working on the primary platform of Google Cloud Platform, deploying models, and integrating them into production applications and Java-based streaming pipelines. They will also be involved in monitoring model behavior in production, benchmarking, and performance testing.

Responsibilities:

Evaluate and benchmark new ML inference frameworks
Deploy models to Google Cloud Platform and integrate them into production applications and Java-based streaming pipelines
Own deployment automation end-to-end
Monitor model behavior in production for real end-users
Design and execute benchmarking, performance testing, and quality testing on ML models
Perform model sampling to support quality evaluation and researcher feedback loops
Debug issues across the full stack
Partner with ML researchers to provide benchmarking feedback and guide inference decisions
Adapt rapidly to non-standard and evolving tech stacks across hybrid infrastructure

Requirements:

Bachelors or Masters degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field
Strong foundation in ML inference, deployment, and quality testing
Demonstrated ability to ramp up quickly on new and unfamiliar tech stacks
End-to-end problem-solving mindset
Core ML knowledge sufficient to benchmark models and collaborate with researchers
Experience deploying models in cloud environments, ideally Google Cloud Platform

Good to Have:

Exposure to Java or JVM-based systems
Familiarity with streaming data architectures
Experience in hybrid cloud/on-prem environments