Rippling aims to apply the power of Large Language Models & traditional ML techniques to help managers run companies more effectively by building a knowledge graph of people and work outputs, and layering on tools to better understand company operations and decision-making needs.
Requirements
- Solid programming skills with an emphasis on backend experience and knowledge.
- Our production code base is primarily Python, PySpark, and PyTorch.
- Experience with developing things that use large language models (LLMs) and familiarity with pre-training and fine-tuning techniques.
Responsibilities
- Translate product needs into crisp mathematical formulations (models); train those models; and, with a small team ship them to production.
- Learn how to design scalable machine learning pipelines for data preprocessing, feature engineering, model training, and evaluation.
- You will work with data engineers to collect and preprocess data sets for model training.
- Stay up-to-date with the latest research in ML and related fields, and apply this knowledge to improve Rippling products.
- We are building data & machine learning infrastructure, training custom models and building user facing apps.
- We’re hiring exceptionally smart, autonomous engineers who can communicate complex technical ideas with clarity and precision.
- We work directly with our executive team on product planning & execution.
Other
- Currently enrolled in a M.Sc. or Ph.D. program in computer science or in a related field with at least 1 semester/quarter after their internship is completed
- Excellent communication skills.
- Passion to learn and develop your skills, both in machine learning and software engineering.
- Rippling highly values having employees working in-office to foster a collaborative work environment and company culture.
- For office-based employees (employees who live within a defined radius of a Rippling office), Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role.
