Engineering Manager, Metaflow, Machine Learning Platform
- Vision: Understanding the media business and how technology is changing the landscape will allow you to lead your team by providing clear technical and business context.
- Partnership & Culture: Establishing positive partnerships with both business and technical leaders across Netflix will be critical. We want you to regularly demonstrate the Netflix culture values like selflessness, curiosity, context over control, and freedom & responsibility in all your engagements with colleagues.
- Judgment: Netflix teams tend to be leaner compared to our peer companies, so you will rely on your judgment to prioritize projects, working closely with your partners - the personalization research leaders.
- Technical acumen: We expect leaders at Netflix to be well-versed in their technical domain and be a user of the products we are building, so they can provide guidance for the team when necessary. Proficiency in understanding the needs of research teams and how to bring efficient ML infrastructure to meet those needs will be crucial.
- Recruiting: Building and growing a team of outstanding engineers will be your primary responsibility. You will strive to make the team as excellent as it can be, hiring and retaining the best, and providing meaningful timely feedback to those who need it.
Minimum Job Qualifications
- Experience leading a team responsible for large-scale ML Infrastructure
- Strong product sense – you take pride in building well designed products that users love.
- Outstanding people skills with high emotional intelligence
- Excellent at communicating context, giving and receiving feedback, fostering new ideas, and empowering others without micromanagement
- Willing to take action, without being stubborn - the ability to recognize your own mistakes
- Your team and partners see your humility all the time and diverse high-caliber talent wants to work with you
- 10+ years of total experience including 3+ years of engineering management
- Experience with modern OSS ML frameworks such as Tensorflow, PyTorch, Ray.
- Prior experience building and scaling Python ML infrastructure
- Prior experience in personalization or media ML domains.
- Exposure to Kubernetes or other container orchestration systems
- BS/MS in Computer Science, Applied Math, Engineering or a related field
- ML practitioner leader or individual contributor experience owning end-to-end ML functions for a product domain