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Production ML Engineer: Inference, Deployment & Monitoring

Posted yesterday

quantum technologies usaSan Jose (CA)

SENIORITY

Manager

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About the role

Quantum Technologies. LLC is looking for a Machine Learning Engineer to own the end-to-end ML model lifecycle from post-training through production, including benchmarking, deployment, monitoring, and integration into live production applications. You will work with ML researchers, production engineers, and platform teams in a fast-moving hybrid cloud environment on inference, deployment automation, and production integration with Java-based streaming pipelines.

Before you apply

Applying takes about a minute. These four things decide how fast it moves after that.

Your profile is current

It's what we read first. Occupations, seniority and locations matter more than a long history.

Two examples you can talk through

Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.

A number in mind

What you're on now and what would make you move. We negotiate better when we know both.

Your notice period

Employers plan around it, and it's the question that stalls offers most often.

Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.

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