Engineering Manager, Ads ML Efficiency

Ever wondered what it takes to power the massive machine learning models behind some of the internet's most dynamic ad experiences? At Reddit, we're diving deep into the very core of efficiency, making our Ads ML systems not just brilliant, but also blazing fast, incredibly cost-effective, and robust. We're on the hunt for a leader to spearhead our brand new Ads ML Efficiency team. If you thrive on optimizing complex systems and pushing the boundaries of what's possible in machine learning, this could be your next big adventure.

Overview

Reddit is a vibrant constellation of communities, built on shared interests, deep passion, and mutual trust. It serves as a home for some of the most open and authentic conversations anywhere online. Every single day, millions of users submit, vote on, and comment about topics that matter most to them. With over 100,000 active communities and approximately 126 million daily active unique visitors, Reddit stands as one of the internet's largest and most influential sources of information.

We believe in a flexible workforce. Our doors are open if you live near one of our physical office locations and wish to come in. Don't live close by? No worries at all: this role is a fully remote, truly global opportunity, welcoming talent from across the globe within countries where Reddit has an established presence. We're building a dedicated Ads ML Efficiency function to make model training and inference materially faster, cheaper, safer, and more scalable. As the Engineering Manager for this pivotal team, you will lead a group focused entirely on model optimization, training efficiency, GPU enablement, load testing, model performance tooling, and the crucial efficiency guardrails across our entire Ads ML infrastructure. This role sits right at the intersection of leadership, cutting-edge machine learning, and significant technical impact.

Key Responsibilities

Lead and grow a high-performing engineering team dedicated to Ads ML efficiency, fostering a culture of innovation and collaboration.
Define the technical roadmap and strategy for improving the speed, cost, safety, and scalability of Reddit's Ads ML models.
Drive initiatives around model optimization techniques, ensuring our ML systems operate with peak performance.
Oversee efforts in training efficiency, exploring and implementing advancements in distributed training and data processing.
Champion GPU enablement projects, leveraging hardware acceleration to dramatically improve model inference and training times.
Develop and implement robust load testing methodologies to ensure the resilience and performance of ML systems under various conditions.
Build and refine model performance tooling, providing engineers with the insights needed to monitor and improve ML efficiency.
Establish and enforce efficiency guardrails across Ads ML, ensuring best practices and preventing regressions in performance.
Collaborate closely with other engineering and product teams to integrate efficiency improvements seamlessly into the broader Ads platform.

Requirements

Demonstrated experience leading and managing software engineering teams, preferably within a machine learning or large-scale data environment.
Strong background in machine learning systems, including deep understanding of model training, inference, and optimization techniques.
Proficiency with modern programming languages such as Python, Java, or C++, and experience with ML frameworks like PyTorch or TensorFlow.
Experience with performance tuning, distributed systems, and cloud infrastructure (AWS, GCP, Azure).
Proven ability to drive complex technical projects from conception through to successful deployment.
Excellent communication, interpersonal, and leadership skills, capable of mentoring engineers and influencing technical direction.
Bachelor's degree or higher in Computer Science, Engineering, or a related technical field.

What You'll Gain

The chance to make a profound impact on the efficiency and scalability of machine learning systems used by millions of people daily.
Opportunity to build and shape a critical new function within Reddit's engineering organization from the ground up.
Work with a highly skilled and passionate team in a collaborative and intellectually stimulating environment.
Access to significant resources and data to tackle challenging, high-impact technical problems.
A flexible, remote-first work culture that values autonomy and work-life balance.
Professional growth and development opportunities in one of the most dynamic tech companies today.