Senior Engineering Manager, Model Development Infrastructure, Machine Learning Platform



Software Engineering, Other Engineering
Los Gatos, CA, USA
Posted on Tuesday, March 5, 2024
Netflix is the world's leading streaming entertainment service with 260+ million 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 a seasoned engineering leader to lead one of the broad horizontal teams within our Machine Learning Platform (MLP) org. MLP is chartered to maximize the business impact of all ML practices 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 Model Development Infrastructure team’s charter spans three main areas:
- A scalable Training Platform to develop deep models trained on high-end GPUs
- Metaflow - our popular open-sourced ML Infra solution for Data Scientists
- A new team focused on infrastructure for Foundation and Generative AI models, including customizing, fine-tuning, and serving large language models. This team focuses on all aspects of customizing OSS foundation models & LLMs, including identifying state-of-the-art techniques for hardware acceleration, serving, and optimal ML performance. The leader will need to hire and grow strong talent in this competitive area.
This is a high-visibility role that requires building great partnerships with senior engineering and data science leaders. We are looking for a leader with experience leading ML practitioners or ML platform engineers, so they can be a strong advocate for ensuring the internal customers have a world-class user experience on our ML Platform.


  • Vision: Understanding the entertainment business and how technology is changing the landscape will allow you to lead your team by providing inspiring 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 use products we build, 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 and managers 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 large-scale ML platform/infrastructure teams
  • Experience working with large and foundation models including Generative AI applications and/or infrastructure
  • 12+ years of total experience and 5+ years of management experience, including hiring, leading, and growing other managers
  • Outstanding people skills with high emotional intelligence
  • Excellent at communicating context (written via memo and presentations, and verbal in large meetings), giving and receiving feedback, fostering new ideas, and empowering others without micromanagement

Preferred Qualifications

  • Strategic & analytical thinking skills combined with curiosity, customer-focused empathy, and the ability to build strong relationships with stakeholders
  • ML practitioner leader or individual contributor experience owning end-to-end ML functions for a product domain
  • Familiarity with Python and deep learning frameworks like Pytorch and TensorFlow
  • Experience extracting optimal ML performance from a variety of hardware accelerators including GPUs and TPUs
  • Built platform offerings for ML Researchers, Engineers, and/or Data Scientists
  • MS/PhD in Computer Science, Engineering or a related field
  • Exposure to modern experimentation and A/B Testing methodologies for consumer-facing applications
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 $240,000 - $1,200,000.
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 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 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.