Netflix

Research Engineer

• Design, implement and operate high impact machine learning models
• Partner with researchers, engineers, data scientists, and product managers to identify high-value machine-learning applications
• Translate business intuition into data-driven solutions
• Create scalable, production-ready ML solutions
• Take algorithms from initial concept through deployment in Netflix’s large-scale, real-time systems
• Contribute to better infrastructure for developing and deploying ML models
• Advocate for and apply best practices for availability, scalability, operational excellence, and cost management
• Operate and innovate on growth and commerce algorithms in production
• Validate solutions through offline experiments
• Build online A/B tests for production systems

Research Engineer 4/5 – Member Lifecycle and Monetization

Artist

• Support CG and Generative AI experts in developing content for animated shorts and specials using a GenAI-native pipeline
• Contribute to creating short stories in a fast-paced production environment
• Support CG artists in creating shot-ready characters, props, and environments using generative tools and traditional DCCs
• Build datasets of assets, images, and videos for training and fine-tuning generative image and video models
• Use ComfyUI to generate concept frames, style frames, character explorations, and environment designs from scripts, outlines, or verbal direction
• Test and evaluate generative tooling and emerging technologies
• Test and expand hybrid GenAI/traditional workflows developed by artists and technology teams

CG Experimental Artist

Engineer

• Design, develop, implement, and support technology solutions for content creation at Netflix
• Own the architecture, deployment, and lifecycle of high-performance storage platforms including Dell PowerScale (OneFS) and NetApp (ONTAP)
• Manage file, block, and object workloads across globally distributed sites
• Automate storage infrastructure provisioning and configuration using Terraform and infrastructure-as-code practices
• Build and own observability for the storage fleet, including metrics, logging, tracing, dashboards, capacity and performance monitoring, and proactive alerting
• Design and build services that improve experiences and productivity for post-production, animation, visual effects, and other creative populations
• Develop, script, and automate production-system solutions
• Deploy solutions and ensure successful integration with existing system architecture
• Participate in storage upgrades, data migrations, and troubleshooting
• Identify potential issues and implement solutions that ensure system reliability and stability
• Collaborate with engineering teams, internal and external partners, technical creatives, production teams, and business and product teams

Systems Development Engineer 5 – Creative Compute, Storage

Technical Program Manager

• Own programs from inception through delivery and proactively drive progress
• Lead multiple cross-functional programs with product, engineering, design, and data science teams
• Decompose requirements into technical execution plans with measurable milestones
• Optimize scope and schedule, manage cross-functional dependencies, and identify and manage risks
• Communicate progress, status, and insights to stakeholders and executive leadership
• Provide domain expertise and form technical strategies with engineering partners
• Scope and lead Generative AI/ML initiatives
• Identify high-value AI/ML use cases and productionize new AI platform capabilities
• Devise technical approaches to abstract goals
• Identify systems needed for new solutions, align roadmaps, and weigh priorities
• Build relationships and rally teams across Finance, Talent, Legal, Customer Support, Engineering, Product, and Data Science

Technical Program Manager 5 – Content & Business Products

• Take full ownership of programs from inception to delivery, proactively driving progress
• Lead multiple cross-functional programs with product, engineering, design, and data science teams to deliver technical solutions
• Decompose requirements into technical execution plans with measurable milestones
• Optimize scope and schedule, manage cross-functional dependencies, and proactively identify and manage risks
• Communicate progress toward goals and report status and insights to stakeholders and executive leadership
• Provide domain expertise to form technical strategies with engineering partners
• Scope and lead Generative AI/ML initiatives, identify high-value use cases, and productionize new AI platform capabilities
• Devise technical approaches to abstract goals using technical, organizational, and communication skills
• Identify systems involved in new solutions, align roadmaps, and weigh relative priorities
• Build relationships and rally teams across Finance, Talent, Legal, Customer Support, Engineering, Product, and Data Science
• Operate independently and challenge the status quo

Technical Program Manager 4 – Content & Business Products

Manager

• Develop and draft ads policy across one or more functional areas, such as financial services, healthcare, and alcohol
• Proactively identify business-critical issues and opportunities to improve how Netflix advises, aligns, and finalizes ads policies
• Advocate for Ads Policy needs using a global lens and balance scalability, localization, nuanced sensitivities, and cultural perspectives
• Work cross-functionally with Advertising, Product Management, Engineering, Legal, Global Affairs, and Strategic Planning and Analysis
• Deliver thoughtful advertising experiences that protect members and business partners while driving outcomes for advertisers
• Collaborate closely with advertisers, legal, and sales teams
• Translate complex policy issues into simple, clear language

Manager, Advertising Policy

Content Manager

• Define and drive the multi-quarter product vision and strategy for Content Ingestion & Distribution
• Own products for unified direct delivery via APIs, web portals, and standards-based feeds
• Lead spec-agnostic ingestion, partner onboarding and permissioning, metadata capture, and automated asset evaluation and QC
• Own distribution orchestration, automation, catalog architecture, and fulfillment to business platforms and systems
• Partner with operational teams to translate pain points into prioritized backlogs and product strategy
• Use operational KPIs to guide product investment and reduce turnaround time, issues, and manual steps
• Work with partner domains to streamline asset workflows and launches
• Hire, coach, and develop Product Managers; set goals and raise product craft standards
• Drive cross-functional alignment across Rights, Encoding Technologies, Localization, Content Foundations, Member Product, and Operations
• Communicate product context and opportunities to engineers, stakeholders, and senior leadership

Group Product Manager, Content Ingestion – Distribution

Systems Engineer

• Maintain the Hawkins Core layer and integrate system context and components into prototyping tools
• Activate eligibility and contribution criteria to manage how domain libraries extend and graduate patterns into Core
• Partner with engineering to normalize taxonomy and capabilities between design and code
• Codify visual and motion standards into scalable, reusable tokens and shared motion principles
• Coordinate major releases across product domains with XD, PM, and Engineering stakeholders
• Partner with domain system designers to centralize agentic context for Commerce, Games, and Member
• Govern documentation, interaction patterns, accessibility (WCAG 2.2 AA), and naming conventions
• Collaborate with embedded system designers to streamline contribution workflows, audit adoption across Figma and codebases, and define centralization versus domain autonomy

Systems Designer, Design Foundations

• Drive early-stage, high-ambiguity programs spanning generative AI product experiences, new interaction modalities, and new discovery surfaces from concept through production
• Support mature, highly cross-functional initiatives within Engagement Intelligence
• Set milestones, manage dependencies, and align engineering, applied science, product, and partnerships teams around shared plans
• Coordinate with external device, platform, and distribution partners on integration timelines, technical requirements, and joint delivery milestones
• Support content expansion into new formats and modalities as Netflix's catalog grows beyond traditional video
• Weigh technology, cost, and business priorities and help teams make tradeoffs
• Apply knowledge of the ML project lifecycle to plan paths from prototype to production
• Build program rituals including roadmaps, status updates, risk reviews, and launch readiness
• Write status updates, decision documents, and alignment artifacts for engineers through senior leadership

Technical Program Manager 5 – Engagement Intelligence

Account Manager

• Lead payment and device product implementations with APAC partners to drive member acquisition and optimize member experiences across partner devices and platforms
• Lead end-to-end project implementations and strategic initiatives with internal and external stakeholders
• Resolve technical challenges and build strong partnerships that drive co-innovation
• Scale Netflix Smart TV feature innovations and adoption through key distribution channels
• Drive partner bundle offers that include Netflix subscriptions and enable billing through partners
• Negotiate, implement, and iterate on Netflix discovery placements and purchase experiences across partner devices and digital platforms
• Drive technology innovation and execution, including API integrations, with partner product and engineering teams
• Contribute to APAC partnerships growth strategy through testing, learning, and evolving product and technology execution
• Lead cross-functional efforts informed by local market challenges and opportunities
• Travel for partner and internal team meetings as needed

Partner Engagement Manager

Machine Learning Engineer

• Build, prototype, and iterate on supervised machine learning models predicting campaign delivery outcomes, including delivery risk, reach, frequency, and contention
• Model demand-side campaign outcomes using supply-side signals such as targeting, frequency caps, contention, and pacing
• Design offline and online evaluation frameworks for accuracy, robustness, distribution shift, and improvement over the simulation baseline
• Own feature engineering and contribute to the team feature store using ad-serving logs, campaign attributes, and supply signals
• Ensure model explainability and interpretability for sales and media-planning stakeholders
• Partner with ML engineers to deploy models at scale and monitor model health and drift
• Collaborate with product, engineering, and sales to define objectives, constraints, and trade-offs and drive adoption of ML-driven forecasts
• Communicate technical decisions, trade-offs, and results to technical and non-technical audiences

Machine Learning Scientist 5 – Forecasting Aggregation

Full-stack Engineer

• Work with Engineering Leadership to set the longer-term technical strategy and architecture for shared policy models, lifecycle and governance services, evaluation paths, and consumer integration contracts.
• Establish reliability, scalability, security, and operational standards for systems used across campaign planning, creative review, serving, Live workflows, forecasting, and reporting.
• Identify technical gaps and opportunities across teams, communicate their business impact, and influence roadmaps toward solutions that optimize for Netflix rather than a single local system.
• Remain hands-on by producing code, designs, prototypes, strategies, and architecture that simplify systems and accelerate delivery.

Software Engineer 6 – Ads Policies

Infrastructure Engineer

• Shape the architecture and evolution of a shared policy model, management service, APIs, and evaluation platform
• Build intuitive authoring workflows that make complex policy rules understandable and safe to create, review, and change
• Design versioned contracts and integration patterns that allow systems across the ads lifecycle to consume policy decisions consistently
• Develop explainability and observability capabilities, including reason codes, decision traces, and operational metrics
• Lead incremental migrations from localized policy logic to shared platform capabilities while protecting correctness and availability
• Partner with Policy, Product, Design, Operations, and engineering teams to clarify requirements, resolve trade-offs, and deliver end-to-end outcomes
• Mentor teammates and contribute to architecture, engineering practices, and the long-term direction of the team

Full-Stack Software Engineer 5 – Ads Policy Infrastructure

Engineering Manager

• Own the charter and technical direction
• Set the platform's technical strategy and roadmap
• Lead and grow a high performing team
• Make sharp build, adopt, or partner calls
• Turn the new hard problems into primitives
• Operate as part of the AI Platform leadership team

Senior Engineering Manager – Agent Platform, AI Platform

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