[Hiring] Machine Learning Engineering Manager - Ads Engagement Modeling @Reddit

Role Description

The Engagement Modeling Team at Reddit focuses on building machine learning models to drive on-platform user engagement with diverse media and content, with a focus on predictive modeling to improve interactions of click-throughs and video view-throughs. This role offers a unique opportunity to shape and scale Reddit’s Ads prediction models, in alignment with our product goals and driving SoTA modeling advancement.

This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders. We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S.

Responsibilities

• Set Technical Vision and Strategy:
  • Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives.
• Drive Technical Execution:
  • Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
• Lead and Mentor a High-Performing Team:
  • Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
• Collaborate Cross-Functionally:
  • Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
• Innovate in ML Architecture:
  • Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques.

Qualifications

• People Management Experience:
  • Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.
• Set Technical Vision and Strategy:
  • Ability to plan and execute a long-term technical strategy aligned with business objectives.
• Drive Technical Execution:
  • Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
• Lead and Mentor a High-Performing Team:
  • Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
• Collaborate Cross-Functionally:
  • Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
• Innovate in ML Architecture:
  • Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.

Requirements

• At least 2+ years of experience building and managing high-performing machine learning teams, ideally in the Ads domain. Will consider tech lead experience as well.
• Deep ML Expertise: Deep hands-on experience working with machine learning models and deploying them in large-scale production systems.
• End-to-End ML Lifecycle Experience: Proven ability in training, evaluating, and deploying large-scale models.
• 4+ years of hands-on experience with TensorFlow or PyTorch.
• Strategic Thinking: Ability to develop and communicate a clear, compelling technical strategy that supports broader company objectives and addresses the needs of internal customers.
• Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.
• Exceptional Communication & Collaboration: Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners.
• Experience with Ads or Engagement Modeling is a plus.

Benefits

• 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA, and Chicago).
• Competitive salary and equity options.
• Comprehensive health benefits (medical, dental, vision) & workplace perks (home office set up stipend, etc).
• Generous 401k matching.
• Flexible vacation policy.
• Paid parental leave (4+ months).
• Family planning support.
• Paid volunteer time off.