MTS, Research Scientist

About the Role Join a small research team at an AI company building customer-specific models for supply chain systems. You will lead research from early hypotheses through production, combining quantitative modeling with language and reasoning models to improve real-world outcomes. What You'll Do Take research hypotheses through development and deployment of production models. Design forecasting and optimization models for multi-variable environments with changing business objectives. Curate proprietary datasets that capture signals from physical and commercial systems. Combine language model capabilities with purpose-built quantitative models to improve accuracy and adaptability. Retune models as consumer sentiment, product launches, and geopolitical conditions change. What We're Looking For At least 4 years of industry experience in ML research, applied ML, or LLM systems. A PhD in a quantitative field such as computer science, machine learning, or statistics. Experience owning the full research cycle, from hypothesis to a model running in production, and conducting technically deep ML research. Experience with time-series forecasting, mathematical modeling, or optimization, including work beyond logistics or routing. Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow. Strong theoretical grounding in machine learning or theoretical computer science, plus deep experience with LLM fundamentals, systems design, tooling, and evaluation. Experience building ML pipelines, running large-scale experiments, parameter fitting, and data engineering; work beyond application-layer LLM systems such as RAG, agents, or prompt pipelines. Compensation & Benefits Base salary: $200,000 to $300,000 annually. Visa sponsorship is available. Location On-site in San Francisco, California, United States.