Machine Learning Manager - PF&O (Recommendations & Forecasting)

at Reddit
📍 United States
USD 230,000-322,000 per year
MIDDLE
✅ Remote

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Algorithms @ 2 Machine Learning @ 3 Hiring @ 3 Leadership @ 3 People Management @ 3 Mentoring @ 3 Data Analysis @ 3 Experimentation @ 3 System Architecture @ 3

Details

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 101M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.

This position sits on the PF&O team (Recommendations & Forecasting) within the Advertiser Optimization org. The team builds advertiser and sales tools including ML systems and data-driven recommendations to teach advertisers how to use Reddit campaigns effectively, forecasting and planning tools for internal sales and external agency buyers, and opportunities to use AI/ML and Reddit’s communities to rethink the advertiser experience.

Responsibilities

  • Set Technical Vision & Strategy:
    • Define and execute the long-term roadmap for the Auto-Bidding team, balancing innovation, efficiency, and revenue impact.
    • Collaborate with leadership to align technology investments with broader business objectives.
  • Develop & Optimize Recommendation and Forecasting Systems:
    • Oversee design, implementation, and maintenance of high-performance advertiser- and sales-facing products.
    • Ensure systems meet or exceed accuracy goals, advertiser expectations, and reliability standards.
  • Mentor & Grow Your Team:
    • Recruit, mentor, and retain engineering talent.
    • Foster a collaborative, inclusive, high-performing culture with emphasis on technical mentorship and career development.
  • Cross-Functional Collaboration:
    • Partner with Product Managers and other engineering teams to align technical work with product requirements and KPIs.
    • Communicate complex technical concepts to non-engineering stakeholders.
  • Champion Continuous Improvement:
    • Drive best practices for model quality, experimentation, system reliability, and operational excellence.
    • Identify opportunities to increase engineering velocity, reduce costs, and improve system performance.

Requirements

  • Engineering leadership: significant experience managing engineering teams, ideally in machine learning or similarly technical domains.
  • Industry tenure: extensive hands-on experience building and operating large-scale Ads or Marketplace systems.
  • People management & team building: demonstrated success in hiring, performance management, mentoring, and fostering diverse, inclusive environments.
  • Hands-on ML proficiency (preferred): experience with real-time serving systems, model development, and optimization pipelines.
  • Control systems & algorithms: familiarity with PID controllers, multi-armed bandits, reinforcement learning, or other bidding/pricing optimization approaches.
  • Marketplace optimization: experience designing bidding optimization algorithms and conducting A/B tests to evaluate business and marketplace impact.
  • Experimentation & data analysis: knowledge of metric design, experimentation methodologies, and large-scale data analysis.
  • System architecture & scalability: expertise in building and maintaining scalable systems, high-performance serving architectures, real-time streaming, and robust data pipelines.
  • Ads domain knowledge: familiarity with ads delivery, recommendations, targeting, or marketplace optimization systems.
  • Strategic vision and cross-functional collaboration skills.

Compensation & Pay Transparency

  • Base pay range (US-based): $230,000 - $322,000 USD.
  • This role may also be eligible for equity (RSUs) and, depending on the position offered, commission. Final offers depend on skills, experience, and other factors.

Benefits

  • Comprehensive healthcare benefits.
  • 401(k) matching.
  • Workspace benefits for your home office.
  • Personal & professional development funds.
  • Family planning support.
  • Flexible vacation & Reddit Global Wellness Days.
  • 4+ months paid parental leave.
  • Paid volunteer time off.
  • Flexible work arrangements, including remote options.

Other Notes

  • The posting notes interviews in select roles/locations may be recorded, transcribed, and summarized by AI with an opportunity to opt out.
  • Reddit is an equal opportunity employer and provides reasonable accommodations for qualified individuals with disabilities. #LI-Remote