MTS - ML Research Engineer

Omnifold trains custom AI models for each customer's supply chain - purpose-built systems that forecast demand, optimize decisions, and adapt continuously to a changing world. The research team is responsible for the core intelligence that makes this possible: developing new model architectures, curating proprietary data assets, and pushing the boundaries of what ML can do.

You will work on problems that frontier models can't solve. Supply chain dynamics require modeling physical systems and processes.

You will own the full research cycle, from hypothesis to production model, with direct visibility into real-world impact.

You will work at the intersection of machine learning models, optimization, LLM reasoning capabilities, and proprietary data - a combination few research teams are building

Training models for forecasting and optimization across complex, multi-variable supply chain environments

Building and curating proprietary data assets that carry signal about real-world physical and commercial systems

Integrating LLM knowledge and reasoning capabilities into purpose-built models to maximize accuracy and adaptability

Continuously improving model performance as market conditions shift (consumer sentiment, product launches, geopolitical changes, competitive dynamics)

5+ years of industry machine learning engineering, including and experimentation