Netflix

Research Scientist 5 at Netflix focused on Machine Learning and Inference Research. The role involves tackling fundamental research questions, publishing in relevant venues, and translating research into tangible business impact for Netflix's consumer-facing products. The position requires a Ph.D. and experience in applying research to real-world problems, with a strong publication record and demonstrated technical expertise.

Senior Manager leading a team of Research Scientists, ML Engineers, Data Scientists, and Analytics Engineers focused on Multimodal Large Language Models (MLLMs) and agentic systems for deep, complex content understanding. The role involves defining strategy, overseeing end-to-end initiatives, managing and growing a multidisciplinary organization, and establishing best practices for complex algorithmic and agentic systems at Netflix scale.

Lead a team of Research Scientists and Machine Learning Engineers focused on multimodal LLM and audio algorithms for localization at Netflix. The role involves mentoring, strategic planning, and driving the development and productionization of cutting-edge ML systems to enhance global member experience.

Machine Learning Scientist role focused on research and development of LLMs, VLMs, and multi-modal foundations for games, with a strong emphasis on inference efficiency, model optimization (distillation, pruning), and generative visuals. The role involves fine-tuning, alignment, and integrating models for real-time interaction and cost-effectiveness.

Research Scientist at Netflix focused on developing and deploying AI/ML solutions for content promotion and discovery. The role involves end-to-end development, including model training, evaluation, and productization of vision-language and multimodal LLM systems, with a focus on advancing the state of the art and enhancing member experience.

Research Scientist role at Netflix focused on applied AI/ML for member systems, including personalization, recommendations, and search. The role involves driving applied research, conceptualizing and implementing algorithmic solutions, and developing production-ready systems using state-of-the-art techniques like LLM pretraining and fine-tuning.

Research Engineer to research, develop, and iterate on LLM prototypes for member understanding, focusing on evaluation and simulation systems. The role involves driving roadmap, influencing product direction, and collaborating across teams, requiring strong deep learning, LLM, and software engineering skills.

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.

Product Manager for AI Video at Netflix, focusing on capabilities from pitch to post-production. Drives AI/ML product strategy, translating creative needs into technical requirements and collaborating with R&D and engineering to deploy AI models for video production.

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.

Research Scientist at Netflix focused on content understanding and merchandising. The role involves designing and developing models, conducting quality evaluations for algorithms, and applying ML/Gen AI to video, audio, and textual data. The goal is to improve content metadata and the discovery experience for members.

Research Engineer at Netflix to apply ML expertise to design, develop, and scale personalization systems and algorithms for member experiences. This role involves creating production-ready ML solutions, optimizing models, and conducting experiments to improve key business metrics.

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.

Senior Product Designer for AI Enablement at Netflix, focusing on architecting agentic platform experiences and intelligent infrastructure for the Ads Suite. This role involves defining scalable patterns for AI integration, operationalizing agentic workflows, and serving as a quality gatekeeper for AI outputs, bridging design and ML engineering.

Research Scientist role focused on signal privacy for Netflix's ad-supported tier, involving machine learning, statistical modeling, and data analysis with a strong emphasis on privacy-enhancing technologies in ad targeting, ranking, and optimization.

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.

Internship role focused on exploring and improving Gaussian Splatting (GS) for future streaming formats, involving research into model compression, training time reduction, and rendering efficiency.

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 pricing science within a B2C subscription business. The role involves designing and implementing causal inference approaches and ML models to understand the impact of pricing actions on member behavior, conducting elasticity and willingness-to-pay research, and evolving measurement tools. The scientist will partner with Finance & Strategy and Product teams to translate findings into actionable business recommendations and own work from ideation to production systems.

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.

Netflix is seeking a Creative Evaluation Lead, Artwork to bridge creative, product, and technical teams to transform promotional artwork workflows using AI. This role involves contributing to AI R&D, evaluating AI model outputs, executing AI solutions for content launches, building learning loops, translating creative needs into AI opportunities, leading training, and staying updated on AI advancements in imagery. The ideal candidate has extensive creative making experience, familiarity with AI image tools, and experience with QC processes for artwork assets.

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.

Director of Product role at Netflix focused on scaling content understanding systems using AI/ML. The role involves driving product strategy, leading product managers and functional teams (operations, ratings, analysts, editorial) to automate and scale areas like ratings, content analysis, and catalog management. It requires experience with ML/AI solutions, shipping AI-powered products, and understanding of computer vision methods.

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.

Product Manager role at Netflix focused on integrating AI/ML into content platform operations and publishing tools to create personalized experiences, automate asset creation, and optimize content distribution. Requires experience with the ML lifecycle, launching AI-enabled products, and evaluating ML techniques.

Product Manager role at Netflix focused on integrating AI/ML into content platform operations and publishing tools to create personalized experiences and optimize content promotion, localization, and distribution. The role involves building strategic roadmaps, leading incubation of new AI capabilities, and translating AI advancements into scalable products.

Research Scientist role focused on identity modeling for Netflix's ad-tier members, involving machine learning, statistics, and data analysis techniques. The role requires experience in identity graphs, privacy, differential privacy, and anonymization to improve advertiser performance and member experience. Responsibilities include applying ML to business problems, identifying research opportunities, diagnosing data/model assumptions, delivering documented outputs, and serving as a strategic partner to stakeholders.

Machine Learning Scientist to develop, optimize, and deploy scalable ML solutions for content strategy, acquisition, scheduling, and advertising at Netflix. The role involves end-to-end ML model development, from ideation to deployment and monitoring, with a focus on informing content decisions and partnering with cross-functional teams.

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.