Software Engineer 5 on the Model Runtime team at Netflix, focusing on building and optimizing infrastructure for training, alignment (RLHF, DPO, PPO), and serving of ML models, including multimodal and diffusion models. The role involves deep systems programming, distributed training at scale, and performance tuning across the full stack, from PyTorch to GPU kernels.

Senior ML Engineer at Netflix Games focusing on integrating GenAI into game development, including gameplay mechanics, asset generation, NPC behaviors, and internal tools. The role involves optimizing model performance, bridging research and production, and mentoring junior engineers. Requires strong software engineering skills in C++/C# and experience with the ML lifecycle.

Machine Learning Engineer at Netflix focused on optimizing training and inference efficiency for LLMs and Multimodal LLMs within the Globalization team. The role involves designing and building scalable systems, optimizing data pipelines, distributed training, mixed precision, KV cache, batching, and quantization to improve performance, latency, and reliability of ML models for Netflix's global catalog.

Netflix is seeking an experienced Engineering Manager to lead a newly formed AI Observability team. This role will architect, design, develop, and launch a new platform for monitoring ML and GenAI workloads, including LLMs, computer vision, and foundation models. The team will focus on making AI systems transparent, reliable, and production-ready by capturing model inputs, features, predictions, outcomes, and behavior. Key responsibilities include embedding observability by default, driving the end-to-end observability strategy, evolving LLM evaluation frameworks, defining and executing a platform roadmap, and hiring/mentoring a team.

Senior Game Engineer at Netflix focused on integrating Generative AI into gameplay systems to create dynamic and player-responsive experiences. The role involves working with game designers, implementing GenAI features, integrating them into core game systems, developing safety and quality guardrails, and using GenAI for rapid iteration and tool building. Requires strong game engineering experience and applied GenAI skills with LLMs or Diffusion models.

Technical Director for GenAI in the Games organization at Netflix, responsible for driving the engineering strategy, leading teams, developing AI-native gameplay mechanics, and scaling core GenAI capabilities like model inference and fine-tuning pipelines for player experiences.

Lead a team building agentic systems, sandboxes, and internal demos to accelerate learning and adoption of LLMs at Netflix, bridging model development and downstream productization.

Manager for Netflix's Member Experience team within Ads Data Science and Engineering. This role focuses on understanding and optimizing the impact of ad delivery policies on member experience using causal inference and predictive models. The team will build models and workflows to drive ad delivery optimization, balancing revenue, member experience, and advertiser outcomes. The role involves leading a team of ML Scientists, Data Scientists, and Analytics Engineers, fostering partnerships, and ensuring high-quality technical outputs.

Machine Learning Scientist at Netflix focused on building and optimizing the ad tech ecosystem. This role involves designing and implementing ML algorithms for ad quality and performance, training and evaluating models on large-scale production data, and developing evaluation frameworks. The goal is to create data-driven solutions for relevant ad experiences and advertiser results, balancing member experience and revenue.

Engineering Manager for Netflix Ads, focusing on core targeting and signals platforms. This role involves leading teams to build and scale systems for audience and contextual targeting, enabling relevant and privacy-forward ad experiences. It requires partnering with ML teams on advanced models, working on high-scale, low-latency services, and shaping signal activation for targeting, optimization, and measurement. The role emphasizes ownership, rapid execution, and building high-performing teams in a fast-paced environment.

Netflix is seeking CG Experimental Artists to join their pioneering team creating animated shorts and specials using experimental GenAI-native production pipelines. This role will support show-specific workflow and technical needs, shape storytelling and visual aesthetics, and develop new workflows and technologies. Responsibilities include using GenAI tools for concept generation, creating shot-ready assets, building and fine-tuning generative models, and testing/documenting generative tools and workflows.

Netflix is seeking a Distributed Systems Engineer 6 to lead the technical direction of the Decisioning & Optimization team within their ad tech ecosystem. This role involves architecting and scaling real-time ad decisioning systems, including ML model serving infrastructure, ranking, scoring, and optimization under strict latency constraints. The engineer will also drive operational excellence and collaborate with Science and Platform teams to productionize ML algorithms.

Manager role focused on translating GenAI experimentation into production-ready guidance for content production partners at Netflix. This involves consulting on feasibility and value, identifying where GenAI improves quality/efficiency/speed, and grounding the technology in creative and operational constraints. The role will prototype, deliver, optimize workflows, educate teams, and provide feedback to product and innovation teams.

Engineering Manager for Netflix's Trust Services and Enforcement team, focusing on building and scaling fraud mitigation services. This role involves applying Generative AI to enhance detection and counter evolving AI-driven attack vectors, while managing a team and driving cross-functional alignment on security risk posture.

Machine Learning Scientist 5 focused on forecasting and audience research within Netflix Games. The role involves building foundational ML building blocks like embeddings and models, accelerating product development through tools and pipelines, bridging the Netflix ecosystem, designing scalable ML pipelines, and establishing technical standards for ML application in game domains. Requires a PhD and significant experience in leading end-to-end ML projects and navigating large technical organizations.

Netflix is seeking a Conversation Designer to improve the support experience for members and customer service agents by designing conversations for their virtual agent. This role involves creating human-AI multi-turn conversations, crafting prompts, building scalable conversation frameworks, and influencing AI strategy. The ideal candidate has hands-on experience designing for generative or agentic AI, understanding LLM capabilities and limitations, and experience with prompt design and human-in-the-loop AI evaluations.

Machine Learning Scientist role focused on ad ranking and personalization at Netflix, involving designing, implementing, and evaluating ML models and optimization algorithms on large-scale production data. The role requires strong collaboration with product teams and communication of technical results to stakeholders.

Manager for a Data Science and Engineering team at Netflix, focusing on building automated systems and AI/agentic solutions for content launch and promotion. The role involves leading a multidisciplinary team, shaping strategy, and driving execution of end-to-end AI solutions.

Head of Technology for a GenAI-native animation studio, responsible for the end-to-end technology stack including artist tools, production workflows, infrastructure, security, and data platforms. This role involves defining technology strategy, leading engineering teams, enabling creative ambition through AI, and scaling operations for multiple productions. Key areas include generative workflows, asset management, inference/training technologies, data pipelines for model fine-tuning, and secure AI usage.

Software Engineer to build enterprise-wide technology and platforms for an AI-native production environment for animated shorts and specials. The role involves evaluating AI developments, packaging workflows, prototyping, and developing tools for artists and technical directors to support scalable GenAI-native production.

Netflix is seeking Technical Directors for its Inkubator team to create animated shorts and specials using experimental, creative-led, GenAI-native production pipelines. The role involves supporting show-specific workflows, strategizing with artists to develop creative solutions, providing tool support, documenting training materials, and beta testing new tools. A key responsibility is identifying and performing custom fine-tuning for models based on show requirements, integrating both internal and external tooling. The role also involves monitoring artist pain points, troubleshooting data handoffs, evaluating new tool releases, identifying standardization opportunities, and collaborating on compute and workstation requirements.

Machine Learning Engineer focused on MLOps, deployment, and performance optimization for AI-driven game concepts, bridging research and production for cloud and edge environments.

Engineering Manager for Netflix's Search & Voice Systems team, focusing on LLM advancements for content discovery and personalization. The role involves leading a team of engineers, developing roadmaps, and driving innovation in high-traffic distributed systems for search and recommendation experiences.

Machine Learning Engineer at Netflix focused on Ads Inventory Management & Forecasting. The role involves building end-to-end ML model deployment and inference infrastructure for low-latency real-time ad systems, handling large data volumes with Spark, and productionizing predictive models for campaign effectiveness forecasting. It also includes building scalable simulation solutions for inventory scenarios and collaborating with cross-functional teams.

Netflix is seeking a Senior Manager for the Ads Forecasting team. This role will lead a team responsible for building and owning scalable forecasting platforms and models for ad supply, demand, and revenue. The team also develops simulators for campaign setup and ad delivery optimization. The ideal candidate will have deep domain expertise in ad forecasting and simulation, experience leading science/ML teams, and the ability to translate business objectives into analytical solutions.

Engineering Manager for Core Applications AI team at Netflix, focusing on building foundational AI capabilities for member systems, including reward models, entity libraries, LLM post-training frameworks, and utility optimization. The role involves leading a team, setting vision, designing APIs, and partnering with other teams to ensure adoption and integration of shared components.

Netflix is hiring Machine Learning Engineers for their Ads Platform Engineering teams. The role involves building and deploying ML models for low-latency real-time ad systems, focusing on areas like inventory forecasting, ad serving, programmatic interfaces, member experience, and audience targeting. Responsibilities include developing and productionizing predictive models for campaign effectiveness, yield optimization, bid ranking, and dynamic allocation, as well as building scalable simulation solutions. Experience with big data tools like Spark and proficiency in languages like Java, C++, Python, or Scala are required.

Netflix is seeking a Software Engineer for their Machine Learning Platform team to develop and expand their model serving systems, focusing on infrastructure for LLMs and other large foundation models. The role involves building scalable, robust systems for online ML model inference, optimizing for latency and cost, and ensuring high availability and performance. This is a highly cross-functional role partnering with various engineering and data science teams.

Software Engineer on the Machine Learning Platform (MLP) team, responsible for designing and building the platform that powers large-scale machine learning model training, fine-tuning, model transformation, and evaluations workflows for the entire company. Focuses on optimizing systems and models for scale and cost-effectiveness, and designing user-friendly APIs for ML practitioners.

Software Engineer for AI for Member Systems at Netflix, focusing on designing, developing, and scaling machine learning algorithms that power the Netflix experience. This role involves collaborating with researchers and product managers to improve personalization systems, enable offline experiments, and drive the implementation of scalable, production-ready solutions for algorithms. The engineer will also contribute to better software engineering practices and systems.

This role focuses on supporting and streamlining integrations with external partners for Netflix's ad-supported tier. The engineer will act as a technical liaison, providing hands-on support, managing incidents, and contributing to integration-specific code changes. While the role is not directly building AI models, it emphasizes leveraging AI tools to enhance support and integration processes.

Netflix is seeking a Senior Data Scientist with ML and causal inference expertise to lead analytics, data science, and strategy for core personalization algorithms. The role involves partnering with product and engineering teams to shape the personalization roadmap and evolve capabilities powered by advanced ML/AI. Responsibilities include leveraging experimentation and causal inference for insights, building robust metrics and measurement frameworks, and exploring trends in content discovery.

This role focuses on the adoption and support of GenAI tools within an enterprise setting, acting as a subject matter expert for IT support and identity management. The specialist will curate Help Center content, analyze support data, and collaborate with various teams to improve user experience with technology, including GenAI productivity tools. While not directly building AI models, the role heavily involves supporting and optimizing the use of AI tools for the enterprise workforce.

Software Engineer 5 role focused on building an AI-first, autonomous quality platform for global payment and checkout experiences at Netflix. The role involves defining E2E testing strategies, architecting GenAI tools for automation and failure prediction, generating synthetic test data, and integrating test coverage with system observability. Requires expertise in automation architecture, modern web automation tools, and understanding distributed systems.

This role focuses on optimizing supplier operations and workflows within Netflix, with a key emphasis on leveraging AI technologies and intelligent agents to drive efficiency and improve processes. The specialist will be responsible for designing and implementing AI-driven improvements, managing supplier risk, ensuring compliance, and collaborating with engineering teams. While AI tools are mentioned as a means to achieve operational excellence, the core function is not the direct development or research of AI models, but rather the application of AI to existing business processes.

Netflix is seeking a Distributed Systems Engineer to build and scale the core infrastructure for their ad tech ecosystem, focusing on real-time ad decisioning, ML model serving, and optimization systems. The role involves working across the stack from model serving to auction execution and pacing, shipping production systems that directly impact revenue and advertiser outcomes.

Full-stack engineer to build internal tools and dashboards for ad decisioning stack, focusing on observability, debugging, and monitoring of ML model serving, auction mechanics, and campaign delivery.

Manager for Netflix's Ads Identity and Signals team, focusing on developing Identity Science capabilities and extracting signals for ad optimization models. This role involves leading ML Scientists and Data Scientists to drive business use cases like ad measurement, attribution, targeting, and ad ranking/bidding systems.

Netflix is seeking Compositors to join their Inkubator team, focusing on creating animated shorts and specials using experimental GenAI-native production pipelines. The role involves integrating generative AI outputs with CG renders, 2D elements, and other sources into polished, cohesive shots using Nuke and adjacent tools. Responsibilities include collaborating with filmmakers and artists, applying compositing skills, contributing to look development, and documenting workflows. Experience with stylized animation and a familiarity with Generative AI imagery are important, with opportunities to build workflows and refine best practices for hybrid compositing.

Security Engineer specializing in Generative AI (GenAI) Security for workforce-facing initiatives, focusing on third-party solutions like low-code/no-code agents and RAG enterprise search. Responsibilities include identifying and mitigating GenAI threats, evaluating third-party GenAI products, developing hardening guides, performing technical validation (threat modeling, pen testing), prototyping security automation tools, and conducting build-vs-buy evaluations.

This role is for a Systems Administrator focused on optimizing operational efficiency through workflow automation, system streamlining, and API integrations for enterprise applications at Netflix. While the role involves using and understanding generative AI tools and concepts, its core function is not building AI models but rather integrating and managing systems that may leverage AI.

Software Engineer L5 to own and evolve automated CI/CD and validation infrastructure for Netflix's Open Connect edge appliances, ensuring security, reliability, and performance. The role involves improving failure triage with AI-assisted tooling and leading engineers.

This role focuses on designing and executing experimental frameworks for Netflix's ads business, developing predictive algorithms, and optimizing marketplace dynamics. It involves transitioning from manual analysis to scalable, automated solutions and applying advanced causal inference and machine learning techniques to drive business decisions and global expansion. The role is considered AI-related due to the use of ML and causal inference, but the primary output is an experimentation platform and business insights rather than core AI model development.

This role focuses on building intelligence and data-driven insights to address fraud and enhance consumer product security at Netflix. The engineer will analyze patterns, identify new signals for anomaly detection, and develop data solutions for fraud prevention, leveraging expertise in security and fraud prevention.

Machine Learning Scientist role at Netflix focused on building and productionizing forecasting models for subscription revenue, ARPU, and member base. The role involves scenario modeling, contributing to the forecasting pipeline, and partnering with business leaders to translate model outputs into recommendations. Requires expertise in time series and regression methods, production systems, Python, SQL, and ML libraries.

Staff-level Software Engineer for Netflix's Evidence Engineering team, focusing on building and operating large-scale, low-latency distributed systems for real-time asset delivery and personalization. The role involves technical leadership, platform evolution, and collaboration with ML scientists and product teams to enhance customer-facing experiences.

This role supervises production for animated shorts and specials using experimental GenAI-native pipelines, managing schedules, tracking, and workflows that blend generative AI with traditional tools. The Production Supervisor ensures projects stay on budget and schedule, supports artists in using new workflows, and collaborates with tech teams to refine processes and tools for feature-quality content creation.

Software Engineer 5 role focused on maturing and expanding Research platforms, data products, and frameworks at Netflix. The role involves leveraging software and data engineering skills to build scalable, performant, and maintainable systems that support quantitative and qualitative researchers. Key responsibilities include designing and building distributed infrastructure, developing integrations with data platforms and experimentation systems, and enabling data scientists by creating scalable methods and utilities. The role requires proficiency in SQL, Python, or Spark, experience with data pipelines and cloud platforms, and an understanding of privacy-preserving techniques. A strong emphasis is placed on observability and owning the solutions built.