Remote ML Platform Engineering Manager (Training & Serving)

Socket.dev; United States; On-site; USD 204,000 - 290,000; Full time

Benefits offered by this job

Health coverage

EspP - Employee Stock Purchase Plan

Tech spending stipends

Generous time off

Job summary

Affirm is seeking an Engineering Manager to lead the ML Training & Serving team. You will guide a group of platform engineers, combining people leadership with strong technical judgment in ML infrastructure.

Work with ML modeling, product, and infrastructure to shape roadmaps and ensure the platform supports Affirm’s ML priorities. We value a remote-first culture with strong cross-functional collaboration and a focus on reliable, cost-effective infrastructure.

Qualifications

• 7+ years of software and/or ML engineering experience with 2+ years in people management.
• Experience building and operating production ML or distributed systems infrastructure.
• Understanding of ML data needs, training datasets, data quality and reproducibility.

Responsibilities

• Define and execute the roadmap for ML training and serving, including training, deployment workflows, GPU infra and low-latency serving.
• Lead, coach, and grow a team of platform engineers while staying engaged in technical decisions.
• Drive delivery and reliability of the infrastructure, balancing reliability, developer experience, performance and cost.
• Evaluate and adopt modern ML infrastructure capabilities as needs evolve (transformers, GPU compute).
• Collaborate with ML modeling, product, and infra teams to support high-priority ML initiatives.
• Recruit, develop, and retain high-performing platform engineers.

Skills

People management

ML infrastructure

Production systems

GPU infrastructure

Leadership

Cross-functional collaboration

System design

Education

Bachelor's degree in a technical field

Tools

TensorFlow

PyTorch

Job description

Affirm is seeking an Engineering Manager to lead the ML Training & Serving team. You will guide a group of platform engineers, combining people leadership with strong technical judgment in ML infrastructure.

Work with ML modeling, product, and infrastructure to shape roadmaps and ensure the platform supports Affirm’s ML priorities. We value a remote-first culture with strong cross-functional collaboration and a focus on reliable, cost-effective infrastructure.