Engineering Manager, Ads ML Efficiency

Reddit is seeking a senior-level Engineering Manager, Ads ML Efficiency to lead a dedicated function focused on making model training and inference faster, cheaper, safer, and more scalable across the USA. This IT leadership role offers a salary of $230,000 within Reddit's flexible workforce model, allowing remote work in any country where the organization has a physical presence, alongside optional access to physical offices.

Core Responsibilities for the Ads ML Efficiency Manager

• Hire, mentor, and retain a high-performing team of ML and systems-oriented engineers.
• Define and execute the roadmap for training optimization, inference optimization, and launch-readiness tooling.
• Drive measurable reductions in model training time, online latency, serving cost, and infrastructure-driven launch risks.
• Partner closely with ranking, ML Platform, and serving teams to remove production bottlenecks.
• Guide the development of profiling, benchmarking, load testing, observability, and efficiency certification systems.

Requirements and Qualifications

Candidates must hold a Bachelor's degree and bring 5 or more years of professional experience to the position. Applicants need deep ML engineering experience close to models, direct hands-on optimization background in training loops or GPU utilization, strong managerial ability, and distributed systems fluency for production-scale ML environments. Strong communication skills and customer instincts are essential, while prior experience in ads ranking, recommender systems, or marketplace ML is strongly preferred. Bonus qualifications include experience with PyTorch, distributed training frameworks, kernel performance optimization, and GPU migrations.