研究工程师 4/5 - 会员生命周期与变现
Research Engineer 4/5 - Member Lifecycle and Monetization
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，将难以想象的事情变为现实。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带来的不适感与兴奋感。加入我们，成为未来的一部分。
会员生命周期与变现数据科学与工程团队在 Netflix 中扮演着关键角色，通过利用数据、实验和机器学习，推动并加速全球会员和收入的可持续增长，开发引人入胜且具有说服力的注册后转化和变现体验，以优化每位会员的收入。这些领域的机器学习是一个相对空白的领域，具有从0到1的应用潜力，可在 Netflix 的规模下带来数百万美元的影响。
我们正在寻找一名研究工程师加入团队，参与运营，并在生产环境中对增长和商务算法进行创新，通过运行离线实验进行验证，并构建在线 A/B 测试以在生产系统中运行。你将与其他 ML 工程师、科学家和产品经理合作，开展跨职能的 ML 项目。
要在这个职位上表现出色，你需要有涉及机器学习的大规模应用经验，具备良好的软件工程原则和设计意识，拥有出色的沟通能力，并能在大型跨职能团队中高效工作。
在此职位中，你将：
- 设计、实现并运营高影响力的机器学习模型
- 与跨职能团队紧密合作，包括研究人员、工程师、数据科学家和产品经理，识别机器学习的高价值应用场景，将业务直觉转化为数据驱动的解决方案
- 与科学家和工程师密切合作，创建可扩展、生产就绪的 ML 解决方案，将算法从初步概念推进到部署到 Netflix 大规模、实时系统中
- 参与更好基础设施的开发，用于开发和部署 ML 模型
- 在可用性、可扩展性、运营卓越性和成本管理方面倡导并应用最佳实践
你将带来的：
- 计算机科学或相关领域的学位
- 4年以上全职工程经验
- 好奇心强、自我驱动，并热衷于解决开放性问题
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.
The Member Lifecycle and Monetization Data Science & Engineering team plays a critical role for Netflix in driving and accelerating sustainable growth of members and revenue globally, by leveraging data, experimentation & machine learning to develop compelling and persuasive conversion and monetization experiences post-signup to optimize revenue per member. Machine Learning in these areas is a relatively greenfield area, and comes with the potential for 0-1 applications that can drive millions of dollars of impact at Netflix’s scale.
We are looking for a research engineer to join the team to contribute to operating, as well as innovating on growth and commerce algorithms in production, validating through running offline experiments, and building online A/B tests to run in production systems. You’ll partner with other ML engineers, scientists and product managers on cross-functional ML initiatives.
To excel in this role, you should have experience with large-scale applications involving machine learning, a good sense of software engineering principles and design, possess strong communication skills, and the ability to work well in large cross-functional teams.
In this role, you will:
- Design, implement and operate high impact machine learning models
- Partner closely with cross-functional teams, including researchers, engineers, data scientists, and product managers, to identify high value applications of machine learning, translating business intuition into data-driven solutions
- Work closely with scientists and engineers to create scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment in Netflix's large-scale, real-time systems.
- Contribute to the development of better infrastructure for developing and deploying ML models
- Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management
What you’ll bring:
- A degree in Computer Science or a related field
- 4+ years of full time engineering experience
- Curious, self-motivated, and excited about solving open-ended challenges at Netflix.
- Excellent software design and development skills in multi-language settings with Scala, Java, and Python and software engineering best practices (e.g. version control, testing, code review, etc.)
- Exceptional communication skills, able to explain complex technical concepts clearly to cross-functional partners
- Broad understanding of core machine learning concepts and their application in large-scale, real-world machine-learning systems
- Familiarity end-to-end machine learning pipelines (e.g. training or production deployment) and common challenges like explainability.
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.