Director, AI/ML Engineering

StockX•Detroit, MI

7h•$225,000 - $275,000

About The Position

Help empower our global customers to connect to culture through their passions. Join a team of ML Engineers and Applied Scientists shaping how millions of buyers and sellers experience StockX. From finding the right product to detecting counterfeits, you’ll tackle new challenges across our Live, Listings, and Core businesses—and turn advances in AI/ML into real marketplace impact. Reporting to the VP of Engineering, you’ll set the AI/ML engineering strategy, build and develop the team, and make the decisions that move our highest-impact opportunities forward. You’ll partner with Product, Data Science, and business leaders to decide where we invest, what we build, and how we measure success.

Requirements

10+ years of relevant, hands-on experience in ML engineering or applied science, with a track record of building and operating production ML systems.
7+ years of practical ML or data science experience, including experience in computer vision, multi-modal learning, search, or recommendation systems.
5+ years of engineering leadership experience, including hiring, developing talent, and leading multiple complex workstreams.
Experience owning an AI/ML roadmap and delivering measurable customer or business outcomes through cross-functional partnerships.
Strong technical judgment across model design, architecture, experimentation, and cloud infrastructure, with the ability to balance performance, speed, and cost.
Clear, compelling communication and the ability to influence senior leaders, make tough prioritization decisions, and turn ambiguity into action.

Nice To Haves

Experience managing managers or leading multiple ML engineering or applied science teams.
Marketplace, e-commerce, or Supply Chain experience, particularly in search, recommendations, computer vision, or fraud and trust and safety.
Advanced degree in Computer Science, Machine Learning, or a related field; experience with AWS and shared ML platforms.

Responsibilities

Own the AI/ML engineering strategy and roadmap, connecting technical investments to customer needs and business priorities.
Build and develop a high-performing team of ML engineers and applied scientists, growing technical leaders and managers as the organization scales.
Lead delivery across search, recommendations, pricing, forecasting, fraud detection, and counterfeit detection.
Set technical direction, guide architecture and model decisions, and choose the right approach—from classical ML to generative AI.
Drive rigorous experimentation and A/B testing to measure impact and focus resources on what works.
Scale ML platforms and MLOps practices that help teams ship quickly, reliably, and cost-effectively.
Own hiring, performance, resource planning, and investment tradeoffs; align senior stakeholders on priorities and results.