软件工程师 5 – 培训平台，AI 平台
Software Engineer 5 – Training Platform, AI Platform
在Netflix，我们的使命是娱乐全世界。我们正在书写下一章——突破叙事、全球粉丝和将不可想象变为现实的边界。我们是一支梦想团队，痴迷于探索创意、直觉和尖端技术融合时会发生什么的令人不安的兴奋感。加入我们，成为未来的一部分。
Netflix是全球领先的流媒体娱乐服务，拥有超过190个国家的2.78亿付费会员，他们可以随时随地在任何联网屏幕上观看或游玩各种类型和语言的电视剧、电影和游戏。
机器学习/人工智能推动了业务各个领域的创新，从通过个性化帮助会员选择适合他们的内容，到更好地理解我们的观众和内容片单，再到优化支付处理和其他以收入为导向的举措。构建高度可扩展且具有差异化的ML基础设施是加速这一创新的关键。
机会
我们正在寻找一位在分布式模型训练及规模化运行所需系统方面有深厚专业知识的高级工程师。你将参与塑造我们训练平台的架构，提升大规模训练任务的性能和可靠性，并为ML工程师构建直观的平台体验。我们的基础设施基于Kubernetes、Ray集群和PyTorch分布式训练原语。
此职位需要扎实的技术深度、良好的工程判断力以及跨团队影响的能力。你将与ML工程师、研究人员、基础设施团队和平台利益相关者紧密合作，识别需求，主导技术讨论，推动一致性和交付高影响力的功能。
目标是通过高度可靠且灵活的AI工具和基础设施，最大化Netflix所有AI用例的业务影响，支持个性化推荐、工作室算法、虚拟制作、增长智能和内容需求建模等关键产品功能。
在此职位中，你将：
· 设计并构建支持公司内所有大规模机器学习模型训练、微调、模型转换和评估工作流及用例的平台
· 共同设计并优化系统和模型，以扩大规模并提高机器学习模型的成本效益
查看英文原文
At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.
Netflix is the world's leading streaming entertainment service, with 278 million paid members in over 190 countries, enjoying TV series, feature films, and games across numerous genres and languages. Members can watch or play as much as they want, anytime, anywhere, on any internet-connected screen.
Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to better understanding our audience and our content slate, to optimizing our payment processing and other revenue-focused initiatives. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation.
### The Opportunity
We are looking for a senior engineer with deep expertise in distributed model training and the systems required to operate it at scale. You will help shape the architecture of our training platform, improve performance and reliability for large training jobs, and build intuitive platform experiences for ML engineers. Our infrastructure is built on Kubernetes, Ray clusters, and PyTorch distributed training primitives.
This role requires strong technical depth, sound engineering judgment, and the ability to influence across teams. You will partner closely with ML engineers, researchers, infrastructure teams, and platform stakeholders to identify needs, lead technical discussions, drive alignment, and deliver high-impact capabilities.
charter is to maximize the business impact of all AI use cases at Netflix through highly reliable and flexible AI tooling and infrastructure that supports key product functions such as personalized recommendations, studio algorithms, virtual productions, growth intelligence, and content demand modeling among others.
**In this role you will get to:**
- Design and build the platform that powers large-scale machine learning model training, fine-tuning, model transformation and evaluations workflows and use cases from the entire company
- Co-design and optimize the systems and models to scale up and increase the cost-effectiveness of machine learning model training
- Design easy-to-use APIs and interfaces for experienced ML practitioners, as well as non-experts to easy access the training platform
### Minimum Job Qualifications
- Design, build, and operate platform infrastructure, libraries, and SDKs for large-scale model training. Enable reliable and efficient training workflows for foundation models and generative AI models of all sizes.
- Diagnose and optimize the performance of large distributed training jobs, including GPU utilization, memory efficiency, communication overhead, data loading, checkpointing, fault tolerance, and cluster utilization.
- Experience with cloud computing providers, preferably AWS
- Comfortable with ambiguity and working across multiple layers of the tech stack to execute on both 0-to-1 and 1-to-100 projects
- Adopt and promote best practices in operations, including observability, logging, reporting, and on-call processes to ensure engineering excellence.
- Excellent written and verbal communication skills
- Comfortable working in a team with peers and partners distributed across (US) geographies & time zones.
### Preferred Qualifications
- Understand modern and real-world Machine Learning model development workflows and experience partnering closely with ML modeling engineers. Lead technical design reviews, facilitate cross-functional discussions, communicate tradeoffs clearly, and align stakeholders on platform direction and execution priorities.
- Familiarity with cloud-based AI/ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI, etc.)
- Familiarity with distributed training performance analysis tools and techniques, such as PyTorch Profiler, NVIDIA Nsight Systems, GPU telemetry, communication profiling, or cluster-level utilization analysis.
- Experience with large-scale distributed training and different parallelism techniques for scaling up training, such as FSDP and tensor/pipeline parallelism
- Expertise in the area of Generative AI, specifically when it comes to training foundation models, fine-tuning them, and distilling them to smaller models
Generally, 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 $466,000.00 - $750,000.00. This compensation range will vary based on location.
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 details about our Benefits [here](https://jobs.netflix.com/work-life-philosophy).
Netflix is a unique culture and environment. Learn more [here](https://jobs.netflix.com/culture).
[Inclusion](https://about.netflix.com/en/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 diversity builds 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.