MTS - ML Research Engineer

Omnifold • San Francisco, CA

1d • Onsite

About The Position

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. This role is interesting because you will work on problems that frontier models can't solve, as 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.

Requirements

• 5+ years of industry machine learning engineering, including and experimentation
• Experience with time-series forecasting, mathematical modeling, optimization, or related domains
• Understanding of LLMs, including fundamentals and practical system design including tool use and eval design
• Experience working with messy, heterogeneous real-world data
• Experience working with large code bases
• Comfort operating in a fast-moving, early-stage environment where research directly feeds production systems

Nice To Haves

• Academic or industry research experience preferred

Responsibilities

• 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 This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed