Full-Stack Engineer 5 - Ads ML & Optimization Tooling

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified last checked Jun 13, 2026

Salary

Not verified not verified - source not recorded; timestamp not recorded

401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

Was this benefit information wrong? Tell us.

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Full-Stack Engineer 5 - Ads ML & Optimization Tooling New York,New York,United States of America | Los Angeles,California,United States of America | Los Gatos,California,United States of America At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next. Our Team The Decisioning & Optimization engineering team sits within the Ad Serving & Decisioning org at Netflix Ads. We own the systems that power real-time ad decisioning, delivering relevant, high-quality ads while balancing revenue goals, advertiser outcomes, and member experience. Our work spans ML model serving infrastructure, ranking and scoring, auction mechanics, budget and pacing systems, and goal-based delivery optimization along with podding, traffic shaping models, and more. As our systems grow in complexity and scale, we are investing in tooling and observability to make the decisioning stack fully legible to engineers, data scientists, and ad operations. We are looking for a full-stack engineer with strong analytical instincts and an observability mindset to build the tools and dashboards that make the stack debuggable, measurable, and self-service. What You'll Do Design and build end-to-end internal tools and dashboards that give the team visibility into the ad decisioning stack, from model inference through different stages of auction Build an ad decision debugger: trace the full

Read the full description at explore.jobs.netflix.net. FewerJobs shows a source-linked preview and links to the original posting.