Senior Machine Learning Operations Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Offered From the posting source checked Jun 20, 2026
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

Offered From the posting source checked Jun 20, 2026

Learning budget

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Verification

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Machine Learning Operations Engineer New York, NY #WeAreParamount on a mission to unleash the power of content… you in? We've got the brands, we've got the stars, we've got the power to achieve our mission to entertain the planet - now all we're missing is… YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter - both for our audiences and our employees - and aim to leave a positive mark on culture. Overview We're hiring a Senior Machine Learning Operations Engineer to own the operational layer around our personalization and recommendation Machine Learning (ML) systems. Our models retrain and deploy daily on automated pipelines. Your job is to make sure we can trust what's running, know when something is off, and fix it fast. You'll sit within DevOps and work closely with ML engineers, who own the models end-to-end. You won't be building infrastructure from scratch, you'll partner with DevOps and Platform Engineering to get the tooling you need, then own it day-to-day. What You'll Do Own model traceability: Every model in production should have clear lineage: what data trained it, what code produced it, what validation it passed, and how it's performing. Evaluate and recommend tooling for versioning, metadata, and model registry, and work with MLEs to drive adoption. Build end-to-end monitoring: Monitor the full signal path: data arrival, feature distribution

Read the full description at careers.paramount.com. FewerJobs shows a preview and links to the original posting.