Netflix

Full-Stack Engineer 5 - Decisioning & Optimization

Netflix$320K — $500K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years of professional software engineering experience in production systems
  • Proficiency in modern UI frameworks (React preferred), TypeScript/JavaScript, and Node.js
  • Experience in building scalable backend systems using Java, Kotlin, or similar JVM languages
  • Built observability tooling or debugging tools for complex distributed systems
  • Strong analytical mindset focused on self-service investigation and decision-making
  • Comfortable with data manipulation and visualization across SQL, streaming data, and time-series metrics
  • Experience in instrumenting or tracing request paths in multi-service architectures

Responsibilities

  • Design and build internal tools and dashboards for ad decision visibility
  • Create an ad decision debugger to trace ad requests and outcomes
  • Develop model serving observability metrics like inference latency and score distributions
  • Build campaign delivery monitoring tools, including spend tracking and pacing visualizations
  • Manage the UI and BFF layer for experimentation platforms with counterfactual results visualization
  • Establish diagnostics, logging, and telemetry frameworks for system performance visibility
  • Collaborate with engineers and data scientists to improve tooling experiences

Benefits

  • Comprehensive Health Plans including Mental Health support
  • 401(k) Retirement Plan with employer match
  • Stock Option Program
  • Disability Programs
  • Health Savings and Flexible Spending Accounts
  • Family-forming benefits
  • Life and Serious Injury Benefits
  • 35 days of annual paid time off for hourly employees
  • Flexible time off for salaried employees
Full Job Description

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 path of an ad request (features, model scores, ranking, auction, delivery, billing) and surface why a particular ad was selected at a particular bid price

  • Build model serving observability: inference latency, score distributions, fallback rates, feature coverage, and calibration health across dozens of concurrent models

  • Build campaign delivery monitoring tools: spend tracking dashboards, frequency cap compliance views, pacing curve visualization, underspend and overspend alerts

  • Own the UI and BFF layer for experimentation and testing platforms, visualizing counterfactual results and offline vs. online comparison

  • Develop and maintain diagnostics, logging, and telemetry frameworks that provide deep visibility into system performance, model serving health, and campaign outcomes

  • Engage directly with engineers, data scientists, and ad ops to gather feedback and continuously improve the tooling experience

Skills & Experience We're Seeking

  • 7+ years of professional software engineering experience building production systems, with meaningful full-stack experience across UI, BFF/API layer, and backend services

  • Proficiency in modern UI frameworks (React preferred), TypeScript/JavaScript, and Node.js

  • Experience building scalable backend systems in Java, Kotlin, or similar JVM languages

  • Built observability tooling, operational dashboards, or debugging tools for complex distributed systems

  • Strong analytical mindset with a bias toward building tools that enable self-service investigation and decision-making

  • Comfortable with data: can query, aggregate, and visualize large datasets across SQL, streaming data, and time-series metrics

  • Experience building tools that instrument or trace request paths through multi-service architectures

  • Product mindset that is deeply empathetic to user needs, strategic in orientation, and driven by outcomes

Nice to Haves

  • Ads domain experience: worked on ad serving, delivery, or marketplace systems and understands the operational data they produce

  • Built model serving monitoring tools: inference latency dashboards, score distribution tracking, fallback and calibration health views

  • Experience with observability platforms: metrics, logging, tracing stacks at scale

  • Familiar with marketplace dynamics: auction behavior, pacing anomalies, budget delivery patterns, and the tooling needed to diagnose them

Generally, our compensation structure consists solely of an annual salary; we do not have 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, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $320,000.00 - $500,000.00.

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 programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

About Netflix

Netflix, Inc. is an American media company founded on August 29, 1997 by Reed Hastings and Marc Randolph in Scotts Valley, California, and currently based in Los Gatos, California, with production offices and stages at the Los Angeles-based Hollywood studios (formerly old Warner Brothers studios) and the Albuquerque Studios (formerly ABQ studios). It operates an eponymous over-the-top subscription video on-demand service, which showcases acquired and original programming as well as third-party content licensed from other production companies and distributors. Netflix is also the first streaming media company to be a member of the Motion Picture Association.
Learn more about Netflix
Size
11,300 employees
Market Cap
$127.6 billion
Industry
Net Income
$2.7 billion
Founded
1997
5 Year Trend
+27.5%
Revenue
$24.9 billion
NASDAQ

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