Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.
Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365—all within 90 seconds.
Based in San Francisco, CA, Rippling has raised $1.2B from the world’s top investors—including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock—and was named one of America's best startup employers by Forbes.
About the role
We are seeking a highly skilled and experienced leader to join Rippling’s Applied Machine Learning team. We are using machine learning and large language models to build software which helps our customers operate their businesses more effectively. You will manage a blended team of machine learning modelers, infrastructure experts, and software engineers. This team is building data and algorithm-driven products, as well as ML-driven features in existing Rippling products. Successful individuals on our team tend to operate with autonomy and alacrity, with strong customer empathy, and an ability to drive outcomes across the entire engineering stack from data ingestion through modeling and into production.
What you will do
Manage a team of engineers responsible for going from product ideation to data acquisition to modeling to serving customers in production.
Attract, recruit, hire, and develop a high-performing ML team.
Drive technical excellence, operational maturity, and code quality within your team.
Provide strong leadership to the engineering team, fostering a culture of collaboration, innovation, and continuous improvement.
Get your hands dirty, and build things with us.
What you will need
Ph.D. or equivalent in Computer Science, Engineering, Mathematics, or related field AND 6 or more years full-time Software Engineering work experience; OR
10 years full-time Software Engineering work experience, which includes 6+ years of software engineering experience in one or more of the following areas: advertising, recommendation systems, risk/fraud modeling, or natural language processing.
Proven track record managing and scaling machine learning teams in one or more of the following areas: computational advertising, recommendation systems, risk/fraud modeling, autonomous vehicles, search, natural language processing, or a related field.
Excellent interpersonal and communication skills with the ability to collaborate with diverse stakeholders.
Strong analytical and problem-solving abilities, with a focus on data-driven decision-making.
Experience managing machine learning teams at two or more companies.
Experience with search relevance and search engine infrastructure.
Experience with big data systems in production: eg, Spark, Pinot, Presto.
Rippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email firstname.lastname@example.org
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 above.