MLOps Team Lead

Description

Trax is looking for an AI Engineer to lead our MLOps team and take full ownership of our machine learning infrastructure used to train, evaluate, and deploy our state-of-the-art computer vision models. In this role, you will work closely with other team leads and Product to plan and build the future of Trax’s core AI platform. You will help define technical direction, make long-term architectural decisions, and translate company goals into executable plans, directly impacting Trax’s ability to scale its AI capabilities and the overall success of the company.

About Trax

Trax’s mission is to enable brands and retailers to harness the power of digital technologies to produce the best shopping experiences imaginable. Trax’s retail platform allows customers to understand what is happening on shelf, in every store, all the time so they can focus on what they do best – delighting shoppers. Many of the world’s top CPG companies and retailers use Trax’s dynamic merchandising, in-store execution, shopper engagement, market measurement, analytics, and shelf monitoring solutions at scale to drive positive shopper experiences and unlock revenue opportunities at all points of sale. As pioneers in computer vision, Trax continues to lead the industry in innovation and excellence through development of advanced technologies and autonomous data collection methods. Trax is a global company with hubs in the United States, Singapore and Israel, serving customers in more than 90 countries worldwide. To learn more, visit www.traxretail.com

Requirements

Responsibilities

• Manage and lead the MLOps team, including mentoring, professional development, and day-to-day technical guidance
• Plan and own quarterly roadmaps, sprint planning, task breakdown, and execution, ensuring alignment with company and product priorities
• Design, build, maintain, and evolve ML infrastructure for training, evaluation, and deployment of computer vision models
• Own the end-to-end ML lifecycle in production, including experimentation workflows, training orchestration, model versioning, deployment, and monitoring
• Balance delivery and technical excellence by making architectural decisions and enforcing engineering best practices
• Work closely with research, data, product, and platform teams to move models reliably from research to production
• Actively contribute code to critical components and review design and implementation across the team
• Evaluate and introduce new technologies and tooling to improve scalability, reliability, and developer productivity
  
  

• 3+ years of experience in MLOps, Machine Learning Engineering, or a closely related role, with hands-on ownership of production ML systems
• Previous experience leading a team or acting as a technical lead, including planning, prioritization, and delivery ownership
• Strong proficiency in Python and common ML frameworks
• Strong software engineering background with experience building and maintaining production-grade systems
• Solid understanding of system design, data structures, and scalable architecture
• Excellent communication skills with the ability to align technical execution with business goals
• High curiosity, strong learning mindset, and comfort operating in a fast-changing technical environment
  
  

• Experience operating ML systems in cloud environments (AWS, GCP, Azure)
• Hands-on experience with Kubernetes, Docker, and large-scale ML workloads
• Experience building and operating backend services and APIs
• Prior experience scaling ML infrastructure for real-time or high-throughput production systems