All roles

Software Engineer L4/L5 - Data and Feature Infrastructure, Machine Learning Platform

Remote · USA Full-time New today

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time. Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to better understanding our audience and our content slate, to optimizing our payment processing and other revenue-focused initiatives. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation. ML models can only be as good as the data we provide them. That's why we continue to innovate on making data and feature engineering as simple, scalable, and efficient as possible. Are you interested in joining us on this mission? You will have the opportunity to build cutting-edge data and feature infrastructure that will power ML models across various domains, including personalized recommendations, payments, games, ads, and more. The Opportunity In this role, you will have the opportunity to build a next-generation ML data and feature platform to significantly improve the productivity of ML practitioners. Our goal is to enable our ML practitioners to easily define and test ML features and labels, while our platform takes care of the computation, storage, and serving of feature values for both high-throughput training and low-latency member-scale inference use cases. You will also have the opportunity to build a centralized feature and embedding store to enable sharing across various ML domains. Unlocking access to these shared datasets will foster innovation through ML in new business areas that otherwise wouldn’t have been feasible. You will collaborate closely with ML practitioners and domain experts to ensure that our models are built with high-quality features and labels. You will also get to work with the broader Machine Learning Platform organization to deliver a cohesive end-user experience that significantly improves the productivity of ML practitioners. Here are some examples of the types of things you would work on:

  • Design and build a near-real-time feature computation engine to generate ML features for both high-throughput training and low-latency inference applications.
  • Operate and manage the feature computation pipelines and feature serving infrastructure for various ML models across multiple ML domains.
  • Build and scale systems that accelerate training through performant data loading, transformation, and writing.
  • Create frameworks to streamline and expedite the availability of new data for training and serving.
  • Develop feature stores that enable feature discovery and sharing.
  • Increase the productivity of ML practitioners by making it easy to define and access features and labels for experimentation and productization.

Minimum Qualifications

  • Experience in building ML or data infrastructure
  • Strong empathy and passion for providing a fantastic user experience to ML practitioners
  • Experience in building and operating 24/7 high-traffic and low-latency online applications
  • Experience with large-scale data processing frameworks such as Spark, Flink, and Kafka
  • Experience in working with and optimizing Scala and/or Python codebases
  • Experience with public clouds, especially AWS
  • Self-driven and highly motivated team player

Preferred Qualifications

  • Experience in building and operating ML feature stores
  • Experience with Functional Programming
  • Experience working with Notebooks such as Jupyter or Polynote

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 $100,000 - $720,000. Netflix provides comprehensive benefits, including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, a 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 salaried employees are immediately entitled to flexible time off. See more details about our Benefits here. Netflix has a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled. Apply tot his job Apply To this Job

Related roles

Applied Machine Learning Engineer Lead Consultant

Remote · USA Full-time

[Remote] Sales Engineer - AI/ML Advanced Data Architecture

Remote · USA Full-time

Principal ML/AI Architect - AI for Member Systems (AIMS)

Remote · USA Full-time

Lead Data & AI Architect

Remote · USA Full-time

Senior Project Manager (Data Science)

Remote · USA Full-time

AI/LLM Architect

Remote · USA Full-time

Enterprise Risk Management Analyst

Remote · USA Full-time

Malware Analyst San Antonio, TX

Remote · USA Full-time

Mid-level Malware Reverse Engineer

Remote · USA Full-time

Insurance Product Management Analyst- Senior (Personal Lines) Remote

Remote · USA Full-time

Experienced Full Stack Customer Service Representative – Amazon Seller Support (Work From Home) Up to $35/hr

Remote · USA Full-time

Senior Insights Analyst (Growth Analytics Team)

Remote · USA Full-time

Experienced Customer Service Representative – Virtual Support Agent (Work From Home)

Remote · USA Full-time

Part-Time Remote Data Entry Specialist – Precision Data Management & Collaborative Support for arenaflex

Remote · USA Full-time

[Remote] Remote - Entry Level Sales (Will Train)

Remote · USA Full-time

Team Lead, SRE

Remote · USA Full-time

New Graduate (May/June 2026) – Power Delivery Engineer

Remote · USA Full-time

Product Manager, Customer Service - Remote Part-Time Opportunity with Netflix's Dynamic Customer Support Team

Remote · USA Full-time

Account Director, US Government - [U.S. Region]

Remote · USA Full-time

Experienced Life Insurance Benefits Advisors – Remote Customer Service and Sales Representatives

Remote · USA Full-time