20 days ago
Base Salary
$466k - $750k/yr
Responsibilities
- Develop and expand scalable compute infrastructure for AI/ML applications.
- Build and operate real-time model inference and serving systems for large-scale ML models, generative models, LLMs, and foundation models.
- Improve latency, cost, availability, and performance while resolving infrastructure bottlenecks.
- Perform production hosting, performance tuning, deployment management, and capacity planning.
- Collaborate with engineers, product managers, machine learning engineers, and data and research scientists.
- Promote engineering best practices in observability, logging, and extensible production code.
Requirements
- Experience building high-traffic distributed services and infrastructure for online ML model inference.
- Familiarity with highly available and performant serving of large-scale ML models.
- Understanding of scalable model-serving solutions for generative models and LLMs, including latency and cost reduction.
- Proficiency in object-oriented programming, preferably Java.
- Experience with production hosting, performance tuning, deployment management, and capacity planning.
- Experience deploying ML models with Triton Inference Server, TensorRT, and Docker.
- Experience working with public cloud platforms such as AWS, Azure, or GCP.
- Bachelor’s or master’s degree in Computer Science, Applied Math, Engineering, or a related field.
- Strong communication, collaboration, and problem-solving skills.
Benefits
- Annual salary plus the option to choose the mix of salary and stock options; the stated salary range is $466,000.00-$750,000.00.
- 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.
- Paid leave programs; full-time salaried employees receive flexible time off immediately.
- Equal-opportunity employer with accommodation support available during the hiring process.
Tech Stack
Categories
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).