SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: CAD 209,000 - 269,000 / annual
Affirm is seeking a Senior Engineering Manager to lead the ML Training & Serving platform team. This is a senior technical leadership role with company-wide impact, combining strong people leadership with deep ML infrastructure expertise.
You will directly manage a team of platform engineers, including senior technical leaders, and partner closely with senior individual contributors to shape the platform's technical strategy and direction.
Key responsibilities include:
- Owning the technical strategy and roadmap for ML training and serving infrastructure, covering large-scale model training, deployment workflows, GPU infrastructure, and low-latency model serving at scale
- Leading and growing a team of platform engineers while remaining deeply engaged in technical strategy and architectural decisions
- Evolving ML infrastructure to stay ahead of the frontier, anticipating where AI/ML are heading and building capabilities before they become urgent needs (large-scale transformer training, GPU compute, reinforcement learning, etc.)
- Partnering with ML modeling, product, and infrastructure leadership to ensure the platform accelerates Affirm's critical ML initiatives
- Establishing engineering excellence across reliability, observability, developer experience, and operational rigor
- Recruiting, developing, and retaining world-class platform engineers
Required qualifications:
- 10+ years of software and/or ML engineering experience with significant hands-on software engineering background and 4+ years managing engineering teams
- Deep expertise in large-scale ML infrastructure (model training systems, model serving, deployment workflows, or GPU infrastructure)
- Strong understanding of ML data needs and how data shapes model behavior and platform design
- Fluency with modern ML: deep neural networks, transformers, reinforcement learning, large-scale GPU training and serving
- Strong systems thinking and ability to reason from low-level infrastructure to broad architectural trade-offs
- Track record of building platforms that accelerate ML team productivity
- Proven ability to recruit, develop, and retain high-performing engineers, including coaching senior ICs
- Experience navigating ambiguity and organizational complexity
- Bachelor's degree in a technical field or equivalent practical experience
Applied ML modeling experience is a plus.
