Engineering Manager
Consumer Inference, Machine Learning Platform
Posted on 1/30/2024
Netflix

10,001+ employees

Subscription streaming entertainment service
Company Overview
Netflix's mission is to entertain the world. The company operates a streaming platform for movies & TV shows and has over 222 million subscribers globally.
Consumer Software
Education

Company Stage

N/A

Total Funding

$120B

Founded

1997

Headquarters

Los Gatos, California

Growth & Insights
Headcount

6 month growth

0%

1 year growth

4%

2 year growth

1%
Locations
Los Gatos, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Tensorflow
Pytorch
CategoriesNew
AI & Machine Learning
Requirements
  • Prior experience leading a team responsible for ML infrastructure
  • Strong product sense
  • 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
  • 10+ years of total experience including 3+ years of engineering management
Responsibilities
  • 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
  • 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
  • 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
  • Team Building: Building and growing a team of outstanding engineers will be your primary responsibility
Desired Qualifications
  • 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