ML Research Scientist: Time-Series & Supply Chain Optimization

Omnifold; San Francisco (CA); On-site; USD 130,000 - 160,000; Full time

Job summary

Omnifold is seeking a Member of Technical Staff, ML Research Scientist in San Francisco to work on innovative solutions for supply chain dynamics. The role will focus on developing and optimizing machine learning models, integrating LLM capabilities, and improving model performance based on real-world conditions.

As part of a pioneering research team, you will take ownership of the research cycle and have direct visibility into the impact of your work. A PhD or relevant experience is preferred.

Qualifications

• Strong foundations in machine learning with experience in developing forecasting models.
• Deep understanding of optimization and time-series forecasting.
• Ability to work with messy, heterogeneous real-world data.

Responsibilities

• Design and train models for forecasting and optimization in supply chain environments.
• Build and curate proprietary data assets about physical and commercial systems.
• Integrate LLM knowledge into purpose-built models for accuracy.
• Continuously improve models as market conditions shift.

Skills

Machine learning

Forecasting models

LLM pipelines

Optimization

Time-series forecasting

Data handling

Education

PhD or equivalent research experience

Job description

Omnifold is seeking a Member of Technical Staff, ML Research Scientist in San Francisco to work on innovative solutions for supply chain dynamics. The role will focus on developing and optimizing machine learning models, integrating LLM capabilities, and improving model performance based on real-world conditions.

As part of a pioneering research team, you will take ownership of the research cycle and have direct visibility into the impact of your work. A PhD or relevant experience is preferred.