Job Description
Job Description
This role is on site in San Francisco, five days a week.
We are helping a venture backed company hire a machine learning researcher for its San Francisco office. The company uses machine learning to support financing decisions for consumers and businesses. You would build the predictive models behind its underwriting and financing systems, working with large, messy, real-world datasets that affect actual financing decisions, not only offline experiments.
The work is about 70 percent research and 30 percent production. This is classical machine learning and deep learning for tabular and structured prediction, not large language model wrapper work. The company is hiring for one seat.
What you will do
• Build predictive models for underwriting and financing, using both traditional machine learning and deep learning.
• Work with large, messy, real-world datasets and keep evaluation rigorous, including temporal validation, calibration, and checks for leakage.
• Do feature engineering and interpretability work with tools such as SQL, Pandas or Polars, and SHAP.
• Design the research plan before a model is trained: the question, the holdout, the metrics, and what would count as a real improvement.
• Get models into production, then watch how they behave after launch and retrain when the data drifts.
• Split your time between research and production so the models that ship are ones you would stand behind.
• Explain model behavior and limits clearly to partners who use the results to make financing decisions.
What you need
• 5 to 12 years of machine learning research. Academic lab work counts.
• A Master's or PhD in computer science, math, physics, or a quantitative field, preferably from a top 30 university.
• Experience as an ML researcher, research scientist, or data scientist doing machine learning research and development.
• Experience building predictive models with traditional machine learning and deep learning.
• Rigorous evaluation habits, plus feature engineering or interpretability work.
• Fast career progression.
• You can work on site in San Francisco five days a week.
• Visa transfers such as OPT and H-1B can be considered.
Nice to have
• Experience modeling messy real-world systems, such as in robotics, physics, or chemistry.
• A first-principles approach to hard problems.
• Credit or lending knowledge is not required.
What this search is not
• This search is not for SQL-only data science profiles.
• This search is not for people whose work is mainly large language model wrappers or prompt-only work.
Location
• On site in San Francisco, California, five days a week.
• Full time, direct hire role. Equity is part of the offer.
How to apply
Apply through this posting, or book a time with our team at calendly.com/risehire/30min. We accept applications on an ongoing basis until the role is filled.
Rise Talent Advisors is an equal opportunity employer. We welcome people of all backgrounds.