Ads Conversion Modeling, Machine Learning Engineering Manager

About This RoleAI processing…

Key Responsibilities

• 1
  People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.
• 2
  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.
• 3
  Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
• 4
  Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
• 5
  Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
• 6
  Innovate in ML Architecture: Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.

Requirements

• Model Architectures: Expertise in architecting and implementing deep learning models, with experience in ranking, recommendation, or conversion modeling.
• ML Frameworks: Proficiency with mainstream ML libraries (TensorFlow, PyTorch).
• End-to-End ML Lifecycle: Experience in training, testing, and deploying production-grade machine learning models.
• Data Pipelines: Experience orchestrating large-scale data generation and processing pipelines.
• Ads domain Experience: Experience in interaction of ranking model with rest of Ads systems like bidding, auction, retrieval etc
• Ads Modeling (Preferred): Background in ads modeling or familiarity with engagement prediction models in the ads domain is beneficial.
• 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.
• Technical Domain Knowledge: Experience with Ads conversion modeling, ranking (heavy ranker experience) & recommendations experience is required.
• 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

Perks & Benefits