Machine Learning Data Scientist/Engineer
Ironclad HQ (San Francisco, CA)
Product & Engineering
Ironclad is the leading digital contracting platform for legal teams. By streamlining contract workflows, from creation and approvals to compliance and insights, Ironclad frees legal to be the strategic advisors they’re meant to be. Ironclad is used by modern General Counsels and their teams at companies like Dropbox, AppDynamics and Fitbit to unlock the power of their contracts data. Ironclad was named one of the 20 Rising Stars as part of the Forbes 2019 Cloud 100 list, the definitive list of the top 100 private cloud companies in the world. The company is backed by investors like Accel, Sequoia, Y Combinator and Emergence Capital.
There are a lot of great things about working here, but by far the greatest benefit is the team. We are a group of motivated, mission-driven people who love learning from each other. Our business team comprises attorneys with experience in big law, tech, and finance, and our technical team comprises designers and engineers from places like Palantir, Salesforce, and MIT. We take pride in doing great work and collaborating well with each other. We work hard, but we also like to have fun.
We are looking for an experienced Machine Learning Engineer to build out an intelligent contract platform, requiring machine learned models to extract insights from the contract process and contract text itself. As a Machine Learning Engineer, you'll be working across the team to identify business problems and design and build systems to apply data solutions to them. You'll be building a platform that lets lawyers scale themselves 100x more effectively. This is a chance to bring a two thousand year old profession into the digital age and ship a product to paying users that can’t live without it.
On Your First Day, We'll Expect You To Have:
- At least 3 years industry experience working as a full-time Data Scientist/Machine Learning Engineer designing and implementing predictive models
- Seasoned in feature selection and feature engineering
- Experience training, tuning, and optimizing production ML models
- Experience building or working with teams building data pipelines
It's Great, But Not Required, If You Have:
- Experience working on NLP or other text problems
- Experience using Google Cloud ML tools
- Compose, TensorFlow, ML Engine
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.