AI/ML Software Engineer

4w1 month ago

iTradeNetwork

US · Full-time · $90,000 – $120,000

About this role

At iTradeNetwork, we provide advanced supply chain software and insights tailored to the food & beverage industry. Our mission is clear and ambitious: To feed the world. We are building an AI-first company where AI is the foundation of how we design products and make decisions.

As an Associate AI/ML Full Stack Developer, you’ll be on the front lines building intelligent, production-ready applications that put machine learning at the core of the user experience. You’ll work alongside experienced engineers and data scientists on real problems that make a measurable impact.

You will ship AI-powered full stack applications from model integration to user interfaces using modern frameworks and cloud-native infrastructure. You’ll own end-to-end data pipelines and develop frontend experiences that surface AI-driven insights in intuitive, responsive interfaces.

This role is for someone who wants to grow fast. You’ll develop deep expertise at the intersection of AI/ML and full stack development, all in service of one of the most consequential industries in the world. You’ll ship code that matters and learn from senior engineers while sharing your own perspective.

Requirements

Bachelor’s degree in Computer Science or a related technical field (or equivalent practical experience).
Solid grounding in data structures, algorithms, and object-oriented programming.
Understanding of core AI/ML concepts: supervised and unsupervised learning, neural networks, model evaluation.
Proficiency in at least one backend language — Python strongly preferred given its centrality to the ML ecosystem.
Hands-on experience with web development (React, Angular, or comparable framework).
Comfort with both SQL and NoSQL databases.
A problem-solving mindset and genuine curiosity about how AI can change the way software works.

Responsibilities

Build and ship AI-powered full stack applications — from model integration to user-facing interfaces — using modern frameworks and cloud-native infrastructure.
Partner with data scientists to bring ML models into production: wrapping them in APIs, optimizing inference pipelines, and monitoring performance in live environments.
Own end-to-end data pipelines that support model training, validation, and deployment workflows.
Develop frontend experiences (React or similar) that surface AI-driven insights in intuitive, responsive interfaces.
Contribute to backend services and microservices that power model serving, data ingestion, and business logic.
Participate in code reviews and collaborative design discussions — learning from senior engineers while sharing your own perspective.
Stay current with the AI/ML landscape: new architectures, tooling, and frameworks move fast, and so do we.