About iTradeNetwork

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. From the start, we’ve been dedicated to tackling the most pressing challenges within food and beverage supply chains, delivering innovative solutions and expert support that make a measurable impact.

Our cutting-edge technology helps businesses streamline complex procurement and fulfillment processes, minimize food waste, optimize inventory, manage compliance risk, and scale profitably. We’re proud to serve an elite customer base, including 13 of the top 25 North American grocers, 8 of the top 10 foodservice distributors, and 8 of the top 10 global food and beverage manufacturers.

Today, we're building an AI-first company — meaning AI isn't a feature we bolt on, it's the foundation for how we design products, make decisions, and ship software. Cerena is proof of that in action: powered by the most connected supply chain network in food and beverage, iTradeNetwork's Solution Suite replaces error-prone manual workflows with faster, smarter tools — driving real results for our customers, and ultimately, for the consumers who depend on them.

iTradeNetwork's Leadership Principles

iTradeNetwork’s purpose is to feed the world — and everything we do is guided by the principles below. Every team member is expected to embody and champion these principles across the organization.

Bias for Action

We value speed and avoid analysis paralysis. We develop conviction, make informed decisions quickly, and take calculated risks to maintain momentum — knowing that swift progress is essential for innovation and growth.

Customer Obsession

We work relentlessly to delight our customers. We work backward from their needs to solve pain points and create solutions that surprise and earn their loyalty. We obsess over customers, not competitors.

Data & Metrics Driven

We operate with facts, not opinions. We dive deep into data and use metrics to measure progress, ground every decision in rigorous analysis, and push for clarity and measurable outcomes.

Raise the Bar

We continuously push for improvement — in ourselves, our teams, and the company. We hire and develop exceptional talent, setting ever-higher standards that elevate performance and drive excellence.

Operational Excellence Through Process

We build lasting processes that optimize for efficiency. By developing, testing, and documenting each process, we create consistency and scale through automation, enabling continuous improvement across the business.

Ownership Mindset

We take responsibility for our work and aim for long-term success. We use resources wisely, stay accountable, and roll up our sleeves to get things done — no task is beneath us.

Earn Trust

We build trust through integrity, transparency, and mutual respect. We communicate openly, own our mistakes, listen actively, and remain open to feedback as an opportunity for growth.

JOB SUMMARY

We are building an AI-first company — which means AI isn’t a feature we bolt on; it’s the foundation of how we design products, make decisions, and ship software. As an AI/ML Software Engineer, you’ll be on the front lines of that mission: building intelligent, production-ready applications that put machine learning at the core of the user experience.

This is a role for someone who has built a solid foundation and is ready to take on more. You’ll deliver well-scoped features and services with increasing independence, partner with senior engineers and data scientists on larger initiatives, and deepen your expertise at the intersection of AI/ML and full stack development — all in service of one of the most consequential industries in the world.

Key Responsibilities

Design, build, and ship AI-powered full stack features — from model integration to user-facing interfaces — using modern frameworks and cloud-native infrastructure, with growing independence on well-scoped work.
Partner with data scientists to productionize ML models: wrapping them in APIs, implementing and tuning inference pipelines, and monitoring performance and reliability in live environments.