Senior Engineering Manager, Data Infra, Machine Learning Platform

$190,000 - $190,000/Yr

Netflix - Los Angeles, CA

Full-time - Senior

Los Angeles, CA

Broadcasting and Content Providers

About the position

The Machine Learning Platform (MLP) organization at Netflix is focused on driving innovation across product functions and decision-support needs through the development of scalable and differentiated machine learning (ML) infrastructure. The Data Infrastructure pillar within MLP is seeking a seasoned engineering leader to establish a comprehensive data strategy for ML use cases, build roadmaps for high-leverage opportunities, and lead teams to execute initiatives that significantly impact the business. This role requires collaboration with senior engineering and data science leaders to enhance the user experience for internal customers on the ML Platform.

Responsibilities

• Set up an overall data strategy for all ML use cases at Netflix.
• Build roadmaps focusing on high-leverage opportunities to advance Netflix's ML data infrastructure.
• Lead teams in executing initiatives that generate significant business impact.
• Build scalable infrastructure for ML practitioners to acquire and load data for personalization and recommendation model training.
• Develop data-related frameworks and services for training machine learning models in various content and studio use cases.
• Advance frameworks and services for feature and label definitions, feature engineering, and data transformations.

Requirements

• 10+ years of total experience in engineering, with at least 5+ years in management roles.
• Experience leading large-scale ML platform/infrastructure teams.
• A track record of hiring and growing diverse, highly talented engineers and people leaders.
• Strong strategic and analytical thinking skills combined with customer empathy.
• Excellent communication skills, both written and verbal, for large meetings and presentations.
• Ability to manage a hybrid team across different geographies and time zones.

Nice-to-haves

• Experience with state-of-the-art recommendation model development, foundation model development, or Generative AI model development.
• Experience building platform offerings for ML researchers, engineers, and data scientists.
• ML practitioner experience owning end-to-end ML functions for a product domain.
• Familiarity with modern experimentation and A/B testing methodologies.
• Proficiency in Python and deep learning frameworks like Pytorch and TensorFlow.
• MS/PhD in Computer Science, Engineering, or a related field.

Benefits

• Health Plans
• Mental Health support
• 401(k) Retirement Plan with employer match
• Stock Option Program
• Disability Programs
• Health Savings and Flexible Spending Accounts
• Family-forming benefits
• Life and Serious Injury Benefits
• Paid leave of absence programs
• Flexible time off for salaried employees
• 35 days of paid time off for hourly employees.