Machine Learning Engineer, Ads Personalization

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

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

Not verified

Relocation assistance

Not verified

Childcare support

Offered From the posting source checked Jun 20, 2026

Learning budget

Not verified

Verification

Not verified

Salary

Not verified

401(k) match

Not verified

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

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

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

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

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Machine Learning Engineer, Ads Personalization 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 are seeking a Machine Learning Engineer to join the PlutoTV pod. You will focus on Channel, Guide, and Schedule personalization. Your goal is to make the FAST (Free Ad-supported Streaming TV) experience feel as dynamic as a premium on-demand service. You will help build the models that select which channels appear in the guide and how content is scheduled to maximize viewer session length. This role requires deep knowledge of FAST systems and the unique constraints of linear programming. You will implement features within our GCP stack, leveraging Qdrant for content similarity and Post-training RL to optimize the "Lean-back" viewing experience. Why This Role Matters Modernizing Linear TV: You are part of the team transforming the static EPG (Electronic Programming Guide) into a personalized, data-driven discovery engine. Optimizing the "Lean-Back": Your models help users find something to watch immediately, reducing the friction inherent in "channel surfing." Global

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