Netflix is the world’s leading streaming entertainment service with 238M paid memberships in over 190 countries enjoying TV series, documentaries, and feature films across a wide variety of genres and languages. Machine Learning drives innovation across all product functions and decision-support needs. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation.
The Opportunity
We are looking for an experienced engineering leader to lead the Consumer Inference team in the Machine Learning Platform organization. Our organization is chartered to maximize the business impact of all ML practitioners at Netflix and innovate on ML infrastructure to support key product functions like personalized recommendations, studio innovations, virtual productions, growth intelligence, and content demand modeling among others.
The Consumer Inference team is responsible for building products, libraries, and services that make it easy for researchers to take their offline ML ideas and easily deploy them to various production environments for consumer facing applications. This team plays a critical role in transitioning ML algorithms into products where it can realize value for Netflix. As a part of this role you will lead a team responsible for the following.
Consumer Scale Inference: Libraries and systems that enable flexible and high-performance processing of data and ML models for Netflix’s 238 million members across a diversity of modeling paradigms.
Model Lifecycle Management: Easy deployment, retirement, and configuration of ML models in online and offline environments.
GPU Inference: Increasingly complex ML models have introduced more opportunities to leverage hardware to meet cost-efficiency and performance needs.
ML Observability: Tools for self-service detection and remediation of ML quality issues in production settings.
To be successful in this role you will need the following skills:
- Vision: Understanding where the ML needs across a diverse set of use cases are today and will be in the future 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. You should have some prior experience running ML infrastructure systems at scale.
- Team Building: 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
- Prior experience leading a team responsible for 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
Preferred Qualifications
- 10+ years of total experience including 3+ years of engineering management
- Prior experience working on ML inference or model lifecycle management, ideally at large scale
- Experience with deploying Tensorflow, PyTorch, XGBoost in production.
- Exposure to modern ML serving systems and frameworks, such as Ray Serve, NVIDIA Triton, ONNX runtime.
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 $190,000 - $920,000.
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 salaried employees are immediately entitled to flexible time off. See more detail about our Benefits
here.
Netflix is a unique culture and environment. Learn more
here.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background 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.
