NetflixNE

Software Engineer L5, Offline Inference, Machine Learning Platform

Netflix is the world's leading streaming entertainment service with over 195 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages.

Netflix

Employee count: 5000+

Salary: 100k-720k USD

United States only

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 (ML) is core to that experience. From personalizing the home page to optimizing studio operations and powering new types of content, ML helps us entertain the world faster and better.

The Machine Learning Platform (MLP) organization builds the scalable, reliable infrastructure that accelerates every ML practitioner at Netflix. Within MLP, the Offline Inference team owns the batch-prediction layer—enabling practitioners to generate, store, and serve predictions for various models, including LLMs, computer-vision systems, and other foundation models. One of our most critical customer groups today is the content and studio ML practitioners in the company, whose work influences what we create and how we produce movies and shows you see when you log into the Netflix app.

The Opportunity:

We’re looking for a talented Software Engineer L5 to join the newly formed Offline Inference team. You will design, build, and operate next-generation systems that run large-scale batch inference workloads—from minutes to multi-day jobs—while delivering a friction-free, self-service experience for ML practitioners across Netflix. Success in this role means not only building robust distributed systems, but also deeply understanding the ML development lifecycle to build platforms that truly accelerate our users.

What You’ll Do

  • Build developer-friendly APIs, SDKs, and CLIs that let researchers and engineers—experts and non-experts alike—submit and manage batch inference jobs with minimal effort, particularly in the domain of content and media

  • Design, implement, and operate distributed services that package, schedule, execute, and monitor batch inference workflows at massive scale.

  • Instrument the platform for reliability, debuggability, observability, and cost control; define SLOs and share an equitable on-call rotation

  • Foster a culture of engineering excellence through design reviews, mentorship, and candid, constructive feedback

Minimum Qualifications:

  • Hands-on experience with ML engineering or production systems involving training or inference of deep-learning models.

  • Proven track record of operating scalable infrastructure for ML workloads (batch or online).

  • Proficiency in one or more modern backend languages (e.g. Python, Java, Scala).

  • Production experience with containerization & orchestration (Docker, Kubernetes, ECS, etc.) and at least one major cloud provider (AWS preferred).

  • Comfortable with ambiguity and working across multiple layers of the tech stack to execute on both 0-to-1 and 1-to-100 projects

  • Commitment to operational best practices—observability, logging, incident response, and on-call excellence.

  • Excellent written and verbal communication skills; effective collaboration across distributed teams and time zones.

  • Comfortable working in a team with peers and partners distributed across (US) geographies & time zones.

Preferred Qualifications:

  • Deep understanding of real-world ML development workflows and close partnership with ML researchers or modeling engineers.

  • Familiarity with cloud-based AI/ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI, Vertex) or open-source stacks (Ray, Kubeflow, MLflow).

  • Experience optimizing inference for large language models, computer-vision pipelines, or other foundation models (e.g., FSDP, tensor/pipeline parallelism, quantization, distillation).

  • Open-source contributions, patents, or public speaking/blogging on ML-infrastructure topics.

What We Offer:

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, 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 hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more detail about our Benefits here.

Netflix is 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 diversitybuilds 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.

About the job

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Posted on

Job type

Full Time

Experience level

Senior

Salary

Salary: 100k-720k USD

Location requirements

Hiring timezones

United States +/- 0 hours

About Netflix

Learn more about Netflix and their company culture.

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Netflix is the world's leading streaming entertainment service with over 195 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.

A great workplace combines exceptional colleagues and hard problems.

Freedom and Responsibility

Our core philosophy is people over process. Our culture has been instrumental to our success and has helped us attract and retain stunning colleagues, making work here more satisfying.

Internet entertainment. Global original content. Product personalization.

Our first original series debuted in 2013. Over the following decades, Internet TV will replace linear, and we hope to keep leading by offering an amazing entertainment experience.

Employee benefits

Learn about the employee benefits and perks provided at Netflix.

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Healthcare benefits

Medical, dental, and vision insurance.

Time Away

Our vacation policy is “take vacation” and we actually do. Frankly, we intermix work and personal time quite a bit. Time away works differently at Netflix.

Paid parental leave

We recognize that one of the most special events in an individual's life is the birth or adoption of a child. Our parental leave policy is: "take care of your baby and yourself." New parents generally take 4 - 8 months.

Work, Not Drive

When it comes to your work schedule, commuting doesn’t always sync up and rush hour can be stressful. Work, not drive partners with a rideshare service that provides you the flexibility and focus on work while you commute.

View Netflix's employee benefits
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Netflix

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Netflix hiring Software Engineer L5, Offline Inference, Machine Learning Platform • Remote (Work from Home) | Himalayas