Netflix is one of the world’s leading entertainment services with 278 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.
The Role
Netflix is the world's leading streaming entertainment service, with over 300 million paid members in over 190 countries, enjoying TV series, feature films, and games across numerous genres and languages. Members can watch or play as much as they want, anytime, anywhere, on any internet-connected screen. Machine Learning/Artificial Intelligence powers all of our consumer experience, including content discovery and personalization, identifying and attracting new members to our product, optimizing our payment processing, and much more. More recently, fast-paced innovation in large language models (LLMs) has greatly helped advance state-of-the-art technology in many areas of personalization, including search and recommendation experiences. The Opportunity The Consumer ML Serving team provides the computational platform on which we build nearly all our consumer-facing ML/AI applications. If you’ve seen it, we probably served it! We provide all the building blocks to serve ML at scale, including a real-time model serving platform, an event-driven model and feature compute framework, a distributed compute orchestration engine, and more. Additionally, as we expand to enable LLM innovation in numerous areas of personalization, we’re building model serving infrastructure for LLMs and other large foundation models. We are looking for a strong senior engineer to own and develop our long-term vision. Our systems power some of Netflix's most business-critical models, and we need you to take our ML/AI initiatives to the next level. You will play a highly cross-functional role, partnering with other engineers, product managers, machine learning engineers, and data/research scientists. If you have a passion for building scalable, robust systems, are interested in pushing the envelope in applied ML algorithms, and enjoy seeing a direct line between your work and what our customers see on their screens, we want to talk to you. You may enjoy working with us if you are:- Self-driven and highly motivated to deliver top-tier ML infrastructure while navigating highly ambiguous environments and can execute 0-to-1 projects.
- Eager to learn about new domains and ship high-quality, well-tested code.
- Able to produce generic and optimal solutions while balancing near-term needs.
- Excited to work in a multidisciplinary environment (engineering, algorithms, data engineering/science, and product experimentation).
- Comfortable working in a hybrid team with partners distributed across (US) geographies & time zones.
- Willing to take broad ownership of team responsibilities (building roadmaps, scoping, task breakdowns, etc.)
- Building and operating high-traffic, real-time distributed systems and ML serving infrastructure for LLMs and other large foundation models.
- Supporting large-scale ML models with a direct impact on what customers see.
- Translating the requirements of research scientists into generic platform offerings.
- Delivering systems requiring high availability, throughput, and performance.
- Navigating highly ambiguous environments.
- Taking on and executing zero-to-one projects.
- Leading projects with 3-4 other engineers.
- Building applications in an object-oriented programming language. (We work primarily with Java, and while prior Java experience is not required to interview, you will be expected to become proficient on the job.)
- DevOps for large applications, including performance tuning, optimization, deployment management, and capacity planning.
- Public cloud like AWS, Azure, or GCP.
- You are a proactive, effective communicator and have a strong bias towards action.
- You have a BS/MS in Computer Science, Applied Math, Engineering, or a related field.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background 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.
Skills Required
- Build and operate high-traffic, real-time distributed systems and ML serving infrastructure for LLMs and foundation models
- Support large-scale ML models with direct customer impact
- Translate research scientist requirements into generic platform offerings
- Deliver systems requiring high availability, throughput, and performance
- Execute zero-to-one projects and navigate highly ambiguous environments
- Lead projects with small engineering teams (3-4 engineers)
- Build applications in an object-oriented programming language (primarily Java); become proficient on the job
- DevOps for large applications including performance tuning, optimization, deployment management, and capacity planning
- Experience with public cloud (AWS, Azure, or GCP)
- BS/MS in Computer Science, Applied Math, Engineering, or related field
Netflix Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Netflix and has not been reviewed or approved by Netflix.
-
Fair & Transparent Compensation — Compensation is positioned as “personal top of market” with regular recalibration and broad posted ranges for senior roles that signal the philosophy. The cash‑forward structure and clearly described pay‑mix choices help set expectations on how pay is determined.
-
Equity Value & Accessibility — Employees can choose the mix of cash versus fully vested 10‑year stock options, with grants structured to be retained even after departure. This employee‑directed design increases accessibility and control over equity participation.
-
Healthcare Strength — Health coverage is described as comprehensive across medical, dental, vision, and mental health, with employer funding designed to offset premiums. Additional resources like counseling/coaching and wellness support reinforce breadth in care access.
Netflix Insights
What We Do
Netflix is the world's leading streaming entertainment service with 209 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.







