Engineering Manager, Machine Learning Platform

Role Overview

What You'll Do

• Define and execute the ML training and serving roadmap across model training, deployment workflows, GPU infrastructure, and low-latency serving.
• Lead, coach, and grow platform engineers while staying engaged in technical decisions and execution.
• Drive infrastructure delivery and operational health while balancing reliability, developer experience, performance, and cost.
• Evaluate modern ML infrastructure capabilities, including transformer workloads and GPU compute.
• Collaborate with ML modeling, product, and infrastructure teams on priority initiatives.
• Recruit, develop, and retain high-performing platform engineers.

What We Look For

• 7 or more years of software and/or machine learning engineering experience, including 2 or more years managing engineers.
• Experience building and operating production ML or distributed systems infrastructure.
• Hands-on experience with at least one of model training, model serving, deployment workflows, or GPU infrastructure.
• Understanding of training datasets, data quality, reproducibility, and evaluation data.
• Familiarity with deep learning, transformer architectures, or large-scale training or serving.