MTS - ML Research Scientist

Member of Technical Staff, ML Research Scientist

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.

What makes this job interesting

• 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

What you'll own

• Designing and 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)

What we're looking for

• Strong foundations in machine learning - experience developing and evaluating forecasting models, and LLM pipelines
• Deep understanding of time-series forecasting, optimization, or related domains
• Experience working with messy, heterogeneous real-world data
• PhD or equivalent research experience preferred, but exceptional engineers with relevant industry experience will be considered
• Comfort operating in a fast-moving, early-stage environment where research directly feeds production systems

Location: San Francisco (in-person, 5 days per week)

Omnifold’s Mission

• Every bad forecast has a physical consequence.
• Unnecessary goods are manufactured, shipped, and stored.
• Emergency air freight is needed for misallocated products.
• Poor production planning means workers show up with nothing to do, or work frantic overtime.
• Inefficiency is everywhere.

Our mission is to eliminate waste and accelerate growth for every company with physical products.