Staff ML Software Engineer – Platform Systems

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Netflix

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1997

📱 Media

👥 B2C

Media • B2C

Netflix is a global streaming entertainment company and content producer whose stated mission is "to entertain the world. " It operates a consumer-facing subscription platform offering on-demand TV shows, films, and original programming, and also runs a public careers site emphasizing culture, inclusion, and hiring accommodations. The provided text highlights Netflix’s focus on recruiting talent worldwide, its work-life and culture pages, and its public-facing employer materials.

📋 Description

• Design, build, and operate observability, evaluation, and tooling subsystems for next-generation ML architecture • Prove subsystems on current AIMS operations, including anomaly detection, root cause analysis, and operational automation • Build observability systems providing visibility into model behavior, training pipeline health, serving latency, and data quality • Drive cost optimization across AIMS training and serving infrastructure through increasingly automated frameworks and tooling • Architect reliability improvements across the AIMS AI/ML stack, reducing toil and improving on-call ergonomics • Contribute to the target architecture and migration path for the modernized AIMS AI/ML stack • Coordinate with teams driving the AIMS modernization effort • Evaluate emerging infrastructure patterns, model paradigms, and platform capabilities and translate them into a forward-looking roadmap

🎯 Requirements

• Significant experience designing, building, and operating production AI/ML systems at scale • Experience with training pipelines and familiarity with model serving and online inference under high traffic • Hands-on experience building subsystems for advanced agentic architectures, including memory, trace, eval, and replay pipelines, or orchestration and routing layers • Deep Python expertise • Working proficiency in at least one JVM language: Scala or Java • Proven track record improving AI/ML system reliability, reducing infrastructure costs, and improving operational scalability • Experience building observability and monitoring systems for AI/ML workloads across training, serving, and data pipelines • Strong distributed systems background, including batch processing at scale and real-time serving infrastructure • Experience collaborating with partner teams to drive cross-functional technical programs, manage dependencies, and build consensus without formal authority • High technical judgment and ability to identify patterns, build reusable frameworks, and make pragmatic investment decisions • Ability to operate with incomplete information, scope problems, define approaches, and adjust course • Preferred: familiarity with LLM evaluation, trace, or replay tooling • Preferred: familiarity with feature stores, model serving platforms, and experiment frameworks • Preferred: hands-on experience migrating production AI/ML systems across technology generations • Preferred: applied experience in personalization domains such as recommendation systems, search, or discovery

🏖️ Benefits

• Annual salary-only compensation structure with choice between salary and stock options • Health Plans • Mental Health support • 401(k) Retirement Plan with employer match • Stock Option Program • Disability Programs • Health Savings and Flexible Spending Accounts • Family-forming benefits • Life and Serious Injury Benefits • Paid leave of absence programs • Full-time salaried employees are immediately entitled to flexible time off