Distributed Systems Engineer 6 - Decisioning & Optimization

Netflix; Los Angeles (CA); On-site; USD 499,000 - 900,000; Full time

Benefits offered by this job

Health plans

401(k) with employer match

Flexible time off

Paid leave of absence

Job summary

Netflix is seeking a Senior Technical Leader for the Decisioning & Optimization team in Los Angeles, California. This role involves leading the technical direction of ad decisioning systems, architectural reviews, and troubleshooting. Candidates should have over ten years in building distributed systems, a deep understanding of ML model serving, and experience in ad tech systems. The position offers an annual salary range of $499,000.00 to $900,000.00, along with comprehensive benefits including health plans and a 401(k) retirement plan.

Qualifications

• 10+ years building distributed systems and backend services at large scale; 3+ years in the ads domain.
• Deep experience with ML model serving infrastructure.
• Built and operated core ad tech systems.
• Comfortable at the intersection of engineering, data science, and product.

Responsibilities

• Own the technical direction of the Decisioning & Optimization team.
• Architect and evolve real-time ad decisioning optimization path.
• Scale ads model serving infrastructure.
• Work with Science and Platform teams.
• Build out simulation and containerised testing frameworks.
• Design and implement real-time pacing systems.

Skills

Distributed systems

Backend services

ML model serving infrastructure

Ad tech systems

API design

Technical leadership

Engineering and data science

Resiliency and reliability

Job description

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.

We launched a new ad‑supported tier in November 2022 and are building an in‑house world‑class ad tech ecosystem to offer our members more choices in consuming their content. Our new tier allows us to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences.

Team

The Decisioning & Optimization engineering team sits within the Ad Serving & Decisioning 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.

We are looking for a senior technical leader to own the technical direction of this pod, set the architectural bar, and drive execution on the hardest problems in ads optimization at Netflix. This is a 60% builder / 40% influencer role: you will write code, ship a proof‑of‑concept in your first weeks, and earn the trust of an opinionated senior team while simultaneously setting direction across the organization.

What You’ll Do

• Own the technical direction of the Decisioning & Optimization team: architecture reviews, incident leadership, capacity planning, and scaling
• Architect and evolve the real‑time ad decisioning optimization path: multi‑stage auction, ranking, scoring, bidding, and pacing under strict latency and throughput constraints
• Scale our ads model serving infrastructure to support dozens of concurrent hot‑path ML models with sub‑20 ms P99 inference, including config‑driven model routing, multi‑model lifecycle management, fallback tiers, and calibration serving
• Work closely with Science and Platform teams, ensuring seamless model productionisation and algorithm deployment
• Build out various simulation and containerised testing frameworks to enable offline validation of marketplace changes before live rollout
• Design and implement real‑time pacing systems that drive budget delivery accuracy across campaign lifetimes
• Develop and scale goal‑based delivery optimisation, enabling dynamic allocation of budget and inventory across multiple demand channels to maximise advertiser outcomes
• Drive modularisation and platform‑thinking: build reusable components and clean interfaces that let the team move faster
• Drive operational excellence: reliability, observability, deployment automation, capacity planning, and incident leadership across the optimisation and broader ad serving stack

Skills & Experience We're Seeking

• 10+ years building distributed systems and backend services at large scale; 3+ years in the ads domain
• Deep experience with ML model serving infrastructure: scaling real‑time inference on the hot path at high QPS with sub‑20 ms P99 latency, including model deployment pipelines, feature hydration, and fallback strategies
• Built and operated core ad tech systems: ad servers, bidders, pacers, or ranking and scoring components
• Designed APIs, platform abstractions, and data models that enable seamless interoperability across a multi‑team ads platform
• Strong understanding of ad serving concepts: inventory management, frequency and recency capping, member ad experience quality, and supply‑demand dynamics
• Track record of technical leadership across multiple teams, setting architectural direction and influencing cross‑functional roadmaps
• Comfortable at the intersection of engineering, data science, and product, translating ML research and algorithms into production systems
• Demonstrated ability to operate in the environment which is a mix of big‑tech scale and startup speed, taking projects that normally take years and delivering production‑ready results with tight timelines

Nice to Haves

• Experience with auction mechanics: first‑price, second‑price, reserve pricing, bid shading, and marketplace competition dynamics
• Multi‑stage ranking systems (retrieval, scoring, re‑ranking), podding and ad break planning
• Built or improved budget pacing and delivery control systems
• Yield optimisation, inventory forecasting, dynamic pricing, fill rate optimisation, and demand/supply allocation strategies
• Familiar with CTV constraints: server‑side ad insertion, live event ad serving at scale
• Experience with experimentation infrastructure: A/B testing, holdout groups, interference‑aware marketplace experiments
• Built simulation or counterfactual testing platforms for marketplace or auction systems
• Strong background in resiliency and reliability: ensuring system availability under extreme load (live events, traffic spikes)

Compensation

The compensation structure consists solely of an annual salary; there are no bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top‑of‑market compensation, Netflix relies on market indicators and considers your specific job family, background, skills and experience. The range for this role is $499,000.00 – $900,000.00.

Benefits

Netflix provides comprehensive benefits including health plans, mental health support, a 401(k) retirement plan with employer match, stock option program, disability programs, health savings and flexible spending accounts, family‑forming benefits, and life and serious injury benefits. We also offer paid leave of absence programmes. Full‑time hourly employees accrue 35 days annually for paid time off, to be used for vacation, holidays and sick time. Full‑time salaried employees are immediately entitled to flexible time off. For more details about our benefits, please refer to Netflix’s benefits page.

Equal Opportunity & Inclusion

Netflix is a unique culture and environment. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation or adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal‑opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, colour, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status or military service.