Machine Learning Engineering Manager - Ads Engagement Modeling
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About This RoleAI processing…
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 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team overview: The Engagement Modeling Team at Reddit focuses on building machine learning models to drive on-platform user engagement with diver
Key Responsibilities
- 1Set Technical Vision and Strategy: Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives.
- 2Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
- 3Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
- 4Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
- 5Innovate in ML Architecture: Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques.
Requirements
- 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. Define and execute a roadmap for conversion 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 conversion prediction, leveraging deep learning and advanced ML techniques.
- At least 2+ 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. Proven ability in training, evaluating, and deploying large-scale models.
- 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.
Perks & Benefits
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