AI Engineer

AI Engineer at Trax Retail

Trax is looking for an AI Engineer to join our MLOps team and take a lead role in shaping the core systems that power AI across the company. From low-latency microservices and production-grade ML workflows to developer tooling and Python infrastructure. We care deeply about clean, elegant code and building powerful systems that are a joy to work with.

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.

Requirements

• 2+ years of experience in Software Engineering
• Proficiency in at least one of the following programming languages: Python, Java, C++, C#, Go, Rust.
• A solid understanding of data structures and design patterns.

Responsibilities

• Lead the design and development of Trax’s core AI platform, supporting a wide range of frameworks, models and configurations to best serve our users' evolving needs
• Build tools and workflows for model training, deployment, and monitoring—enabling seamless integration between research and production.
• Collaborate closely with research scientists, data engineers, and product teams to deliver reliable, high-performance AI solutions.
• Shape the Python ecosystem at Trax—defining best practices, building reusable libraries, and developing infrastructure that supports our Python teams.

Advantages

• Experience working with ML frameworks such as pytorch, tensorflow, sklearn, etc
• Experience working with MLOps tools such as airflow, kubeflow, clearml, mlflow, triton, mlserver, etc
• Experience working with cloud environments such as AWS, GCP, or Azure.
• Experience using Kubernetes and Docker.
• Experience with Backend API development.

Key skills/competency

• MLOps
• Python
• Machine Learning
• Data Structures
• Design Patterns
• Kubernetes
• Docker
• Cloud Platforms
• Backend API
• Model Deployment