Staff Machine Learning Engineer
- Collaborate with cross-functional teams to translate business requirements into models.
- Design and develop 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.
- Implement models in our production code base (primarily Python, Go).
- Stay up-to-date with the latest research in ML and related fields, and apply this knowledge to improve Rippling products.
- Ph.D. or equivalent in Computer Science, Engineering, Mathematics, or related field AND 5 or more years full-time Software Engineering work experience; OR
- 5 years full-time Software Engineering work experience, which includes 4+ years of software engineering experience in one or more of the following areas: advertising, recommendation systems, risk/fraud modeling, or natural language processing.
- Comfortable with hands-on programming (eg, Python, Go, Java, C/C++)
- Ability to communicate complex technical ideas with clarity and precision.
Experience with developing things that use large language models (LLMs) and familiarity with pre-training and fine-tuning techniques.
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 40 mile 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.
This role will receive a competitive salary + benefits + equity. The salary for US-based employees will be aligned with one of the ranges below based on location; see which tier applies to your location here.
A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, and location. Final offer amounts may vary from the amounts listed below.