Software Engineer L5 - Offline Inference, Machine Learning Platform

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 $100000 - $720000.

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.