Full-Time Engineering Manager - Ads Retrieval

• Set Technical Vision & Strategy: Define and execute the roadmap for ads retrieval – balancing innovation, efficiency, and business impact.
• Oversee Model & System Development: Guide end-to-end ML model development (data processing, training, deployment) and ensure robust, scalable retrieval systems.
• Mentor & Grow Your Team: Recruit, mentor, and retain top ML talent, fostering a collaborative, inclusive, and high-performing culture.
• Cross-Functional Collaboration: Partner with Product Managers, Data Scientists, and other Engineering teams to align retrieval strategies with product requirements and KPIs.
• Continuous Improvement: Advocate for model quality, system reliability, and operational excellence. Identify opportunities to improve ML engineer velocity and overall performance.

• 2+ years of engineering management experience, leading ML or related technical teams
• 6+ years of industry experience with large-scale ML, ideally in information retrieval, recommendation systems, or ads
• 4+ years of Hands-on expertise with ML frameworks like TensorFlow or PyTorch
• Experience deploying ML models to production and measuring their performance through both technical and business metrics
• Familiarity with ads ecosystems, marketplace dynamics, and candidate retrieval is a major plus

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