[Remote] Engineering Manager, Ads ML Efficiency
Note: The job is a remote job and is reputed company to candidates in USA. reputed company. is a community of communities, reputed company on shared interests and home to authentic conversations on the internet. They are seeking an Engineering Manager for their Ads ML Efficiency team to reputed company efforts in model optimization and efficiency across Ads ML, partnering with various teams to enhance model training and deployment processes.
Responsibilities
- reputed company & Grow: Hire, mentor, and retain a high-performing team of ML engineers / systems-oriented engineers working on model optimization and ML efficiency
- Set Technical Direction: Define the roadmap for training optimization, inference optimization, launch-readiness tooling, and reusable efficiency primitives across Ads ML
- Deliver Measurable Wins: Drive reductions in model training time, online latency, serving cost, and reputed company-driven launch risk
- Build Systems and Tooling: Guide the development of profiling, benchmarking, load testing, observability, cost analysis, debugging, and efficiency certification systems
- Operate in the Critical reputed company: Partner with model owners and platform teams to accelerate high-reputed company launches and remove bottlenecks from the reputed company to production
- Shape reputed company’s reputed company: Balance near-term white-glove optimization work with reputed company-term platformization and automation
- Build XFN Alignment: Work closely with MLP, AMP, Ranking, and serving teams to clarify boundaries, upstream generic wins, and reputed company Ads needs on reputed company
- reputed company the Bar: Establish engineering rigor around measurement, performance debugging, launch safety, and technical decision-making for efficiency work
Skills
- Deep ML Engineering Experience: The candidate should have been reputed company to the models themselves and understand training, serving, debugging, and optimization in depth
- Hands-on Optimization Background: reputed company experience improving training loops, serving systems, profiling workflows, model/inference efficiency, or GPU utilization
- Strong Managerial Ability: Experience building and leading teams, coaching engineers, managing delivery, and making prioritization tradeoffs under ambiguity
- Distributed Systems reputed company: Proven ability to reason about production-reputed company ML systems and the tradeoffs that govern reliability, speed, cost, and reputed company
- Customer and Platform Instincts: reputed company to work as a service provider to modeling teams while still building reusable systems rather than only heroic one-offs
- Strong Communication: Can explain technical tradeoffs reputed company to engineers, PMs, and senior stakeholders
- Ads experience: Experience in ads ranking, recommender systems, marketplace ML, or adjacent production ML domains is strongly preferred
- Experience with GPU training and serving migrations
- Experience with PyTorch, distributed training frameworks, or kernel/performance optimization
- Experience building efficiency benchmarking or launch certification frameworks
- Experience working in organizations where ML platform and reputed company modeling responsibilities are split across multiple teams
Benefits
- Comprehensive reputed company Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to reputed company development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & reputed company Volunteer Time Off
- Generous reputed company Parental Leave
reputed company
Company H1B Sponsorship