TELECOMMUTE Machine learning engineer

3BEES TECHNOLOGIES INC

United States

about 1 month ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Software Debugging Distributed Systems Java Virtual Machine (JVM) Machine Learning E2e Testing Tensorflow Data Streaming Systems Integration Google Cloud Cloud Platform System Performance Testing

+4 more

Pytorch HybridCloud Deployment Automation Machine Learning Operations

Job description

Primary platform: Google Cloud Platform for inference, deployment automation, experimentation, and sampling
Production integration: Java-based streaming pipelines for model integration layer
Infrastructure: Hybrid setup with on-premise streaming and Google Cloud Platform serving stacks
Distributed systems: Working knowledge needed for debugging and end-to-end testing. Deep expertise not required
Machine Learning frameworks: TensorFlow, PyTorch, JAX or similar frameworks, * Evaluate and benchmark new ML inference frameworks to support production decisions
Deploy models to Google Cloud Platform and integrate them into production applications and Java-based streaming pipelines
Take ownership of deployment automation end-to-end - from model handoff to live serving
Monitor model behavior in production for real end-users
Design and run benchmarking, performance testing, and quality testing for ML models
Perform model sampling to support quality evaluation and researcher feedback loops

Requirements

Solid foundation in ML inference, deployment, and quality testing
Proven ability to quickly get up to speed on new and unfamiliar tech stacks - this is the most critical trait
End-to-end problem-solving approach - ability to own an issue from model handoff to user-facing behavior
Core ML knowledge to benchmark models and work with researchers
Experience deploying models in cloud environments, preferably Google Cloud Platform
Exposure to Java or JVM-based systems. Model integration is done in Java, deep expertise not required
Familiarity with streaming data architectures
Experience in hybrid cloud/on-prem environments