Engineering Manager, Ads ML Efficiency
WFA Digital Insight
The demand for skilled engineering managers in AI and machine learning has skyrocketed, with a 25% increase in job openings over the past year. Reddit's commitment to remote work and innovative ML approaches makes this role particularly attractive. As the digital landscape continues to evolve, professionals with expertise in model optimization and efficiency are in high demand. With Reddit's vast user base and commitment to community, this role offers a unique opportunity to drive impact. Before applying, candidates should be prepared to showcase their technical expertise and experience leading high-performing teams.
Job Description
About the Role
Reddit is seeking an experienced Engineering Manager to lead its Ads ML Efficiency team. This role is crucial in optimizing model training and inference, ensuring faster, cheaper, safer, and more scalable operations. The Engineering Manager will be responsible for guiding a team of skilled ML engineers and systems-oriented engineers to identify and address bottlenecks in the Ads ML pipeline.The ideal candidate will have a deep understanding of machine learning engineering, with hands-on experience in model optimization, training efficiency, and GPU enablement. They will be expected to set the technical direction for the team, defining the roadmap for training optimization, inference optimization, and launch-readiness tooling.
Reddit prides itself on its flexible workforce, with options for remote work and in-office collaboration. This role is perfect for individuals who thrive in a fast-paced environment and are passionate about driving efficiency and innovation in machine learning.
What You Will Do
- Lead and grow a high-performing team of ML engineers and systems-oriented engineers
- Define the technical direction for the Ads ML Efficiency team
- Drive reductions in model training time, online latency, serving cost, and infra-driven launch risk
- Guide the development of profiling, benchmarking, load testing, observability, cost analysis, debugging, and efficiency certification systems
- Partner with model owners and platform teams to accelerate high-priority launches and remove bottlenecks from the path to production
- Balance near-term white-glove optimization work with medium-term platformization and automation
- Work closely with cross-functional teams to clarify boundaries, upstream generic wins, and keep Ads needs on track
- Establish engineering rigor around measurement, performance debugging, launch safety, and technical decision-making for efficiency work
What We Are Looking For
- Deep ML engineering experience, with a strong understanding of training, serving, debugging, and optimization
- Hands-on optimization background, with experience improving training loops, serving systems, profiling workflows, model/inference efficiency, or GPU utilization
- Proven experience in leading high-performing teams and mentoring engineers
- Strong technical skills, with the ability to dive deep into complex problems
- Excellent communication and collaboration skills, with experience working with cross-functional teams
- Passion for driving efficiency and innovation in machine learning
Nice to Have
- Experience with cloud-based infrastructure and containerization
- Knowledge of machine learning frameworks and tools
- Familiarity with agile development methodologies
Benefits and Perks
- Competitive salary and equity package
- Flexible remote work options
- Comprehensive health insurance and benefits package
- Generous paid time off and holidays
- Professional development opportunities and conference attendance
How to Stand Out
- Be prepared to showcase your technical expertise in machine learning engineering and model optimization
- Highlight your experience in leading high-performing teams and mentoring engineers
- Emphasize your ability to dive deep into complex problems and drive efficiency and innovation
- Showcase your passion for machine learning and your desire to drive impact
- Research Reddit's company culture and values to demonstrate your alignment with the organization
- Prepare to discuss your experience with cross-functional teams and your ability to communicate complex technical concepts
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