8 days ago
Base Salary
$600k - $1066k/yr
Responsibilities
- Design, build, and operate observability, evaluation, and tooling subsystems for next-generation ML architecture.
- Prove new subsystems in current AIMS operations, including anomaly detection, root-cause analysis, and operational automation.
- Build observability systems covering model behavior, training-pipeline health, serving latency, and data quality.
- Develop frameworks and automation to optimize compute efficiency and reduce training and serving infrastructure costs.
- Architect reliability improvements, reduce operational toil, and improve on-call ergonomics across the AI/ML stack.
- Contribute to the target architecture and migration path for the modernized AIMS AI/ML stack.
- Evaluate emerging infrastructure patterns, model paradigms, and platform capabilities and translate them into a forward-looking roadmap.
- Coordinate technical programs, dependencies, and consensus across partner teams.
Requirements
- Significant experience designing, building, and operating production AI/ML systems at scale, including training pipelines and model serving or online inference under high traffic.
- Hands-on experience building orchestration or control subsystems for advanced agentic architectures, such as memory, trace, evaluation, replay, or routing pipelines.
- Deep Python expertise and working proficiency in at least one JVM language, such as Scala or Java.
- A proven track record improving AI/ML reliability, reducing infrastructure costs, and increasing operational scalability.
- Experience building observability and monitoring systems for AI/ML workloads across training, serving, and data pipelines.
- Strong distributed-systems experience, including batch processing at scale and real-time serving infrastructure.
- Experience driving technical programs across functions, managing dependencies, and building consensus without formal authority.
- Preferred familiarity with LLM evaluation, trace, replay, observability, or debugging tooling.
- Preferred familiarity with feature stores, model-serving platforms, experiment frameworks, and modern AI/ML infrastructure patterns.
- Preferred experience migrating production AI/ML systems across technology generations.
- Preferred applied experience in personalization domains such as recommendations, search, or discovery.
Benefits
- Comprehensive health plans and mental health support.
- 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.
- Paid leave programs; full-time salaried employees are immediately entitled to flexible time off.
- Annual compensation is structured as salary and stock options with no bonuses; the stated annual salary range is $600,000.00–$1,066,000.00 and varies by location.
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About Netflix
Netflix builds and operates a global streaming service for TV series, films, games, and live programming, and produces original content through its in-house studio. It serves consumers in 190+ countries via subscription and ad-supported plans on internet-connected devices. Founded in 1997 and headquartered in Los Gatos, California, Netflix is a public company traded on NASDAQ (NFLX).