Machine Learning Manager

Summary

Join Reddit's Ads Auto-Bidding team as a Machine Learning Manager and lead a team of engineers in developing large-scale, real-time systems for bid optimization and maximizing advertiser value. You will define and execute the team's roadmap, overseeing the design and implementation of high-performance auto-bidding algorithms. Leverage your expertise in control systems, reinforcement learning, and marketplace optimization to design new bidding products and conduct A/B testing. Build scalable systems and data pipelines, while mentoring and leading a high-performing team. Collaborate with cross-functional teams to align strategies and ensure model quality and system reliability. This role requires significant experience in machine learning and engineering management within a large-scale environment, preferably in advertising or marketplace optimization.

Requirements

• Minimum of 2 years of engineering management experience leading ML or related technical teams
• At least 6 years of industry experience with large-scale machine learning, preferably in advertising or marketplace optimization
• Minimum of 4 years of hands-on experience building ML systems
• Proven expertise in marketplace optimization, experimentation and metric design, and data analysis

Responsibilities

• Define and execute the roadmap for the Auto-Bidding team, balancing innovation, efficiency, and business impact
• Oversee the design, implementation, and maintenance of high-performance auto-bidding algorithms and advertiser-facing products (e.g., Target CPA) to achieve optimal campaign performance
• Utilize your experience with control systems, including PID controllers, multi-armed bandits, reinforcement learning algorithms, or bid/pricing optimization systems
• Design new bidding optimization products and algorithms, conduct rigorous A/B experiments to evaluate business impact, and understand the marketplace implications of bidding changes
• Architect large-scale serving systems, data processing pipelines, and real-time processing solutions
• Recruit, mentor, and retain top talent while fostering a collaborative, inclusive, and high-performing team culture
• Partner with Product Managers, Data Scientists, and other Engineering teams to align strategies with product requirements and key performance indicators (KPIs)
• Advocate for model quality, system reliability, and operational excellence. Identify opportunities to improve engineering velocity and overall performance

Benefits

• Comprehensive Health Benefits
• Retirement Savings plan with matching contributions
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation & Reddit Global Days Off