Senior ML Engineer: Production Inference in Hybrid Cloud

Artifintech; San Jose (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Artifintech is seeking a Machine Learning Engineer to own the end-to-end ML model lifecycle from post-training through production in a hybrid cloud environment. You will work with ML researchers, engineers and platform teams in a fast-moving setting.

Responsibilities include benchmarking inference frameworks, deploying models to GCP, automating deployment end-to-end, and monitoring model performance in production. Strong cloud experience, especially with GCP, is required.

Qualifications

• Strong foundation in ML inference, deployment and testing.
• Ability to ramp up on unfamiliar tech stacks quickly.
• End-to-end problem-solving from model handoff to user-facing behavior.

Responsibilities

• Benchmark ML inference frameworks for production.
• Deploy models to GCP and integrate into streaming pipelines.
• Own end-to-end deployment automation from handoff to serving.
• Monitor model behavior in production.

Skills

ML inference

Deployment

Quality testing

Cloud environments

GCP

Java pipelines

Streaming data

Hybrid cloud/on-prem

Technical leadership

Tools

GCP tooling

Java-based pipelines

TensorFlow/PyTorch/JAX

Job description

Artifintech is seeking a Machine Learning Engineer to own the end-to-end ML model lifecycle from post-training through production in a hybrid cloud environment. You will work with ML researchers, engineers and platform teams in a fast-moving setting.

Responsibilities include benchmarking inference frameworks, deploying models to GCP, automating deployment end-to-end, and monitoring model performance in production. Strong cloud experience, especially with GCP, is required.