Soma Capital Portfolio Jobs

Senior Staff Machine Learning Infrastructure Engineer



Software Engineering, Other Engineering
San Francisco, CA, USA
Posted on Wednesday, September 13, 2023
About Rippling
Rippling is the first way for businesses to manage all of their HR & IT—payroll, benefits, computers, apps, and more—in one unified workforce platform.
By connecting every business system to one source of truth for employee data, businesses can automate all of the manual work they normally need to do to make employee changes. Take onboarding, for example. With Rippling, you can just click a button and set up a new employees’ payroll, health insurance, work computer, and third-party apps—like Slack, Zoom, and Office 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, Bedrock, and Greenoaks—and was named one of America’s best startup employers by Forbes (#12 out of 500).
About the Role

We are seeking a seasoned machine learning infrastructure engineer to join Rippling’s newly formed Applied Machine Learning team. As an engineer working on practical applications of large language models (LLMs), you will own the design and implementation of the infrastructure that trains, serves and integrates these models into our products.

You will work closely with product teams across Rippling with the ultimate goal of building tools that help our customers operate their businesses more effectively. The work is necessarily cross-functional – successful individuals on our team have an unusually high degree of autonomy, strong customer empathy and an ability to drive outcomes across the entire engineering stack. Your expertise will contribute to the advancement of our organization's foundational machine learning capabilities and drive innovation in our products and services.

What joining our team now means

Rippling’s Applied Machine Learning efforts are nascent. If you join us now, you’ll be an early team member and help shape:

1. What ML infrastructure stack we choose (technologies & frameworks)
2. The people we hire
3. The direction & focus of our product investments
What you will do
  • 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.
  • You are an expert at building ML infrastructure – having 4+ years of industry experience building infrastructure that handled data preprocessing/transformation, feature engineering/storage and model training/evaluation/deployment/serving.

  • You are a seasoned software engineer – having 10+ years of industry experience building software at some (or all) levels of the stack (foundational infra, backed, ux). You should be able to point to specific products that exist today that wouldn’t have been possible without your contribution.

  • You are comfortable with hands-on programming – Rippling mostly builds in Python, but prior experience in Python is not a hard requirement for this role ( jvm languages/go/ruby/typescript experience should be transferable).

  • You have a knack for communicating complex technical ideas with clarity and precision

Additional Qualifications

  • Experience developing user-facing applications that use large language models (LLMs).

  • Experience with full stack software engineering (distributed systems, services, UX). The more of the stack you can span comfortably, the more effectively you’ll be able to help drive project outcomes.

  • Familiarity with LLM pre-training and/or fine-tuning techniques and infrastructure.

Additional Information

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.