Description

You own ML model inference, deployment, and production quality testing across hybrid infrastructure.

This role is remote.

Responsibilities

• Evaluate and benchmark ML inference frameworks to guide production decisions.
• Deploy models to Google Cloud Platform and integrate them into Java-based streaming pipelines.
• Own end-to-end deployment automation, from model handoff through live serving.
• Design and execute performance and quality testing, including model sampling for researcher feedback.
• Debug issues across the full stack, from the inference layer down to streaming pipelines.

Required Skills

• 10+ years of engineering experience.
• Strong foundation in ML inference, deployment, and quality testing.
• Experience with TensorFlow, PyTorch, or JAX.
• Production experience with Google Cloud Platform (GCP).
• Working knowledge of Java and JVM-based systems for model integration layers.
• Understanding of distributed systems for debugging and end-to-end testing.
• Proven ability to ramp up quickly on new and unfamiliar tech stacks.
• Bachelor's or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.

Preferred Skills

• Exposure to streaming data architectures.
• Familiarity with hybrid cloud and on-premise environments.

Key Skills

Education

Bachelor's or Master's degrees