Director, Machine Learning Engineer, Content

Description

The company makes camera technology and runs a visual messaging app, a subsidiary focused on making computing more human, and other digital services.

The Content Machine Learning Engineering group builds the systems that retrieve and rank personalized content and that judge content for quality, freshness, and relevance in the stories and short-form video feeds.

The team works on multi-modal content understanding, graph representation learning, and content ranking. It refines models with human review and uses advanced personalization methods to improve the short-form video experience and help creators make content more easily.

This role sets the multi-year machine learning strategy for recommendation and ranking, content understanding, production reliability, and experimentation. It also covers growing managers, and tying model investment to business results.

Responsibilities

• Help teams tackle hard technical problems and build strong experiences in the app, on a platform used by over 450 million people every day.
• Run the day-to-day work of the Content ML teams across offices in Seattle, Los Angeles, San Francisco, Palo Alto, and New York.
• Set organization-level goals and lead the technical and organizational roadmap for the engineering team.
• Work with executives, finance, product, and engineering to deliver the highest quality product.
• Shape decisions on architecture and build scalable, reliable, cost-effective engineering solutions.
• Build and grow high-performing teams of software engineers, machine learning engineers, and technical leaders, and mentor engineering managers, directors, and senior individual contributors.
• Move quickly without lowering quality, and raise the bar for operational excellence.

Requirements

• Bachelor's degree in a relevant technical field such as computer science, or equivalent years of practical work experience.
• 10+ years of software engineering experience after your bachelor's degree, or a master's degree in a technical field plus 9+ years of post-graduate software development experience, or a PhD in a related technical field plus 6+ years of post-graduate software development experience.
• 5+ years of experience leading a large team at scale and managing engineering with a focus on efficiency.
• Experience working with ML, AI, and ranking systems.
• Strong understanding of machine learning, deep learning approaches, and algorithms.
• Demonstrated experience leading and developing engineers with diverse backgrounds, skills, and perspectives.
• Ability to work with cross-functional executives and managers across a geographically distributed organization.
• Preferred: track record of delivery in fast-changing, highly collaborative, multi-site, multi-stakeholder environments.
• Preferred: experience with machine learning and generative recommendations.
• Preferred: experience with high-scale ranking and recommendation systems.

Conditions

Work in the office 4+ days per week under the company's default-together policy, which is meant to build culture, reinforce values, and support collaboration.

In the United States, each work location sits in a pay zone that sets the salary range. Starting pay depends on job-related skills, experience, qualifications, work location, and market conditions, and may be negotiable within the range. Pay zones may change in the future.

Zone A (CA, WA, NYC): base salary range of $334,000-$500,000 per year.

Zone B: base salary range of $317,000-$475,000 per year.

Zone C: base salary range of $284,000-$425,000 per year.

This position is eligible for equity in the form of RSUs.

The company is an equal opportunity employer that considers applicants regardless of protected characteristics, and considers qualified applicants with criminal histories in line with applicable law, including local fair chance rules.

Benefits

• Paid parental leave.
• Comprehensive medical coverage.
• Emotional and mental health support programs.
• Compensation packages that let you share in the company's long-term success.