软件工程师 4/5 - 数据与特征基础设施，AI 平台
Software Engineer 4/5 – Data and Feature Infrastructure, AI Platform
在Netflix，我们的使命是娱乐全世界。我们正在书写下一章——突破叙事的边界、全球粉丝文化，让难以想象的事情成为现实。我们是一支充满激情的团队，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兴奋的未知领域。加入我们，成为未来的一部分。
机器学习/人工智能推动着业务各个领域的创新，从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阵容，再到优化支付处理和其他以收入为导向的项目。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。
ML模型的质量取决于我们提供的数据。这就是为什么我们持续创新，使数据和特征工程尽可能简单、可扩展和高效。你是否对加入我们的使命感兴趣？你将有机会构建前沿的数据和特征基础设施，为各种领域（包括个性化推荐、支付、游戏、广告等）的ML模型提供支持。
**职位机会**
在这个职位中，你将有机会构建下一代ML数据和特征平台，显著提升ML实践者的生产力。我们的目标是让我们的ML实践者能够轻松定义和测试ML特征和标签，而我们的平台则负责处理高吞吐量训练和低延迟会员规模推理用例中的计算、存储和特征值服务。
你还将有机会构建一个中心化的特征和嵌入式存储库，以在各种ML领域之间实现共享。解锁这些共享数据集的访问权限将促进新业务领域的ML创新，这些领域之前可能无法实现。你将与ML实践者和领域专家紧密合作，确保我们的模型使用高质量的特征和标签。你还将与更广泛的AI平台团队合作，交付一致的用户体验，显著提升ML实践者的生产力。
**你将参与的一些工作示例：**
- 设计并构建一个近实时的特征计算引擎，为高吞吐量训练和低延迟推理应用生成ML特征。
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.
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.
ML models can only be as good as the data we provide them. That's why we continue to innovate on making data and feature engineering as simple, scalable, and efficient as possible. Are you interested in joining us on this mission? You will have the opportunity to build cutting-edge data and feature infrastructure that will power ML models across various domains, including personalized recommendations, payments, games, ads, and more.
**The Opportunity**
In this role, you will have the opportunity to build a next-generation ML data and feature platform to significantly improve the productivity of ML practitioners. Our goal is to enable our ML practitioners to easily define and test ML features and labels, while our platform takes care of the computation, storage, and serving of feature values for both high-throughput training and low-latency member-scale inference use cases.
You will also have the opportunity to build a centralized feature and embedding store to enable sharing across various ML domains. Unlocking access to these shared datasets will foster innovation through ML in new business areas that otherwise wouldn’t have been feasible. You will collaborate closely with ML practitioners and domain experts to ensure that our models are built with high-quality features and labels. You will also get to work with the broader AI Platform organization to deliver a cohesive end-user experience that significantly improves the productivity of ML practitioners.
**Here are some examples of the types of things you would work on:**
- Design and build a near-real-time feature computation engine to generate ML features for both high-throughput training and low-latency inference applications.
- Operate and manage the feature computation pipelines and feature serving infrastructure for various ML models across multiple ML domains.
- Build and scale systems that accelerate training through performant data loading, transformation, and writing.
- Create frameworks to streamline and expedite the availability of new data for training and serving.
- Develop feature stores that enable feature discovery and sharing.
- Increase the productivity of ML practitioners by making it easy to define and access features and labels for experimentation and productization.
**Minimum Qualifications**
- Experience in building ML or data infrastructure
- Strong empathy and passion for providing a fantastic user experience to ML practitioners
- Experience in building and operating 24/7 high-traffic and low-latency online applications
- Experience with large-scale data processing frameworks such as Spark, Flink, and Kafka
- Experience with data storage and serving technologies such as Iceberg and Cassandra
- Experience in working with and optimizing Java and/or Python codebases
- Experience with public clouds, especially AWS
- Self-driven and highly motivated team player
**Preferred Qualifications**
- Experience in building and operating ML feature stores, such as Chronon
- Experience in building embedding-based retrieval systems
- Experience working with Notebooks such as Jupyter or Polynote
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.