Netflix

Research Scientist

• Focus on cultural foresight and identifying, tracking, and analyzing cultural shifts, emerging trends, and behaviors in key markets, in partnership with Data Science & Engineering teams
• Leverage advanced social listening tools and methodologies to analyze digital conversations, sentiment, and meme culture
• Build strong relationships and collaborations with cross-functional partners and other Consumer Insights groups to ensure that our research meets the business’s needs and empowers the decisions we make for tomorrow
• Connect the dots across complex areas and identify new opportunities to proactively inform stakeholders’ strategy
• Synthesize complex data from disparate sources into compelling narratives, lead socialization, turn insights into actionable recommendations, and refine cultural fluency through the socialization process
• Work with regional insights teams to contextualize global trends with local nuances, ensuring our view of culture is inclusive and world-class
• Innovate and introduce emerging technologies or methodologies to enhance our existing work

Senior Researcher – Cultural Trends, Intelligence

Data Engineer

• Lead the Member Foundations Data Engineering team
• Build the core datasets that represent how members interact with Netflix product
• Influence and guide projects from end-to-end: ideation to production
• Ensure data products are built with engineering rigor and strong data quality guarantees
• Invest in tooling and best practices for achieving goals

Manager, Data Engineering – Member Data Products

Support Engineer

• Support the Delivery Engineering team, which owns the systems used by Netflix engineers
• Monitor and handle customer requests, troubleshoot, solve issues, automate support needs
• Develop runbooks, improve and maintain support tools
• Understand product offerings and continuously look for ways to enhance the engineering support experience
• Work on the development of support automation tooling
• Recommend product and operational improvements based on customer interactions

Solutions Support Engineer – Delivery

Strategy

• Set the merchandising strategy for organizing and presenting Netflix Games
• Build launch promotional programs that highlight Games on-service
• Rapidly learn and iterate through experimentation
• Be a key point of contact for the Games Studio
• Work closely with our operations team for successful promotional campaign launch
• Design merchandising strategies to increase chances of adoption of our games
• Scope and sequence merchandising requirements for games on the product roadmap
• Help navigate the Games promotion needs within the larger Netflix product merchandising ecosystem
• Research new need states for game discovery
• Analyze internal data, market research, and industry trends

Catalog Merchandising Strategy Manager, Games

Data Scientist

• Design and validate measurement frameworks that accurately capture content quality, engagement, and business value across diverse content types
• Autonomously identify measurement gaps and pursue research with significant business impact, making compelling cases for prioritization
• Apply causal inference, observational analysis, and statistical modeling to understand drivers of content value and member satisfaction
• Ensure metrics measure what they intend to, identifying potential biases, edge cases, and unintended consequences before they impact decisions
• Partner across Content, Product, Finance, and Engineering to align measurement approaches with business needs and technical constraints
• Serve as a strategic thought partner to stakeholders, influencing content and product strategy through clear measurement insights
• Contribute to team growth through documentation, mentorship, and knowledge sharing that uplevels skills and practices
• Build well-documented datasets, tools, and analytical frameworks that scale across the organization
• Present research clearly to technical and non-technical audiences at all levels

Data Scientist 5, Content DSE

Product Manager

• Improve ad relevance for Netflix members and drive better advertiser performance by building state-of-the-art ads recommendation ML models and launching them as scalable products
• Define and communicate a clear vision, strategy, and roadmap for ads scoring and ranking that is aligned with Netflix Ads’ broader business goals
• Deliver innovative solutions that empower advertisers and improves user experiences
• Partner with Engineering and Data Science to define robust evaluation metrics for ads ranking systems and auction models
• Leverage data and analytics to uncover growth opportunities, evaluate performance, and make informed decisions about existing or new ad products
• Operate with an agile mindset, willing to rapidly prototype, test and improve our product offering
• Define how we will measure the success and effectiveness of our products, and drive the execution and continuous evaluation of those metrics.

Product Manager, Ads Scoring – Ranking

• Hire, coach, and grow a diverse, high-performing team of data and software engineers
• Develop and execute a clear, impact-oriented roadmap for the team
• Oversee the design, building, and scaling of robust, well-modeled, and reliable data products
• Lead a function dedicated to building reusable data frameworks, development tooling, and automation capabilities
• Define and drive best practices for data modeling, pipeline architecture, testing, and observability
• Act as the primary technical partner to the central Data Platform team
• Build strong relationships with senior stakeholders across various departments
• Provide clear direction and priority alignment in a fast-paced environment

Manager, Data Engineering – Commerce

Research Engineer

• Lead the 0-1 development of the User Identity Knowledge Graph
• Identify and articulate the key challenges and opportunities in modeling user knowledge at scale
• Design, prototype, and deploy novel machine learning and knowledge representation models
• Prioritize and sequence research efforts, balancing long-term vision with near-term impact
• Collaborate with data scientists, engineers, product managers, and stakeholders across Netflix

Research Engineer – User Identity Knowledge Graph

Machine Learning Engineer

• Strategic Model Integration: Evaluation and integration of open-source and commercial models (e.g., for ASR, TTS, diarization, VAD), balancing quality, latency, and cost to accelerate game development.
• Model R&D & Adaptation: Lead the fine-tuning and adaptation of speech models (TTS, Voice Cloning, ASR) using parameter-efficient techniques (e.g., LoRA/PEFT) to address production gaps and creative constraints that external/commercial solutions cannot satisfy.
• Data & Alignment: Lead audio and multimodal data curation, including cleaning, segmentation, labeling, and synthetic data generation to support speech model training and adaptation.
• Scalable Training: Scale speech model training using distributed data pipelines and training strategies for large datasets.

Machine Learning Scientist L4/L5 – Audio & Speech for Games

Cloud Engineer

• Lead and cultivate a world-class team of security experts and software engineers
• Establish strong organizational relationships and connect business context to security needs
• Design and implement strategic high-level cloud security boundaries
• Build scalable security solutions for account management, cloud identity, and access management
• Provide operational security services to achieve cloud security mission

Engineering Manager – Cloud Architecture Tooling, Security

• Apply modeling and machine learning techniques to business problems at the intersection of product and data science
• Autonomously identify and pursue research with significant business impact, and make compelling cases for prioritization and resource allocation
• Diagnose data and model assumptions, curating and testing appropriate models for each dataset and business objective
• Identify, compute and validate the appropriate metrics to measure success
• Deliver well-documented datasets, tools, and reports to key technical and business partners
• Serve as a strategic thought partner to product managers and business stakeholders, directly influencing product direction and improving user experience
• Cultivate strong partnerships with cross-functional stakeholders from product, engineering, operations, design, consumer research, etc
• Effectively communicate findings and insights to both technical and non-technical audiences, driving adoption and understanding of ML-driven solutions.

Data Scientist 5 – Ads Identity

Full-stack Engineer

• Handling impactful availability, scalability, and usability challenges
• Self-defining optimal ways to configure, manage, and observe the growing Open Connect platform
• Implementing microservices to enable analytics, insights, discovery, and visualizations
• Designing orchestration to manage many thousands of globally distributed appliances and devices
• Building data models and APIs to help manage and maintain the fleet
• Understanding the breadth of our multi-tenant platform, creating generalized solutions which can be leveraged across multiple domains - including networking, video, and gaming

Software Engineer, L5 – Open Connect Platform

• Design and build backend services that power the Live MAM platform (e.g., ingest orchestration, media/metadata normalization, rights‑aware APIs, timecode‑based services)
• Integrate a third‑party MAM with Netflix’s hybrid infrastructure, ensuring a coherent media and metadata flow across systems
• Implement robust data models and APIs for live media assets, metadata, rights and restrictions, and time‑aligned events
• Collaborate with partner teams (engineering, production, operations, vendors) to deliver end‑to‑end workflows for live and near‑live content
• Work with AI/ML teams and services to incorporate automated tagging and indexing into the MAM ecosystem
• Own services in production, including observability, reliability, and on‑call, for systems that support time‑critical live workflows

Software Engineer 5 – Live Media Asset Management

• Work collaboratively with data engineers and other partners in the messaging space
• Build reliable, scalable data pipelines using Apache Spark/Flink
• Power analytic dashboards, custom viz applications, A/B experiments, and algo features
• See the problem through a platform lens
• Build scalable, flexible data products

Data Engineer – Messaging

Solutions Engineer

• Monitoring and handling customers’ requests
• Troubleshooting and solving issues
• Automating support needs
• Developing support documentation and runbooks
• Improving and maintaining support tools and automation
• Understanding product offerings
• Continuously looking for ways to improve the engineering support experience
• Advocating for customers, following through on issues and resolving them in a reasonable time
• Providing insights and feedback to improve tools