Machine Learning (ML) Engineer (Chicago)

• LOCATION: REMOTE UNITED STATES
• DEPARTMENT: ENGINEERING
• WORK STATUS: FULL-TIME

Overview

Are you looking for a hybrid or remote work opportunity? Are you interested in a workplace that allows for flexibility in your day? Are you ready for a workplace that provides benefits that suit your needs?

About AI at our company

In the past two years, billions of documents have already benefited from the insights of our AI platform – and we are just getting started on our journey to use AI to improve each user experience, product, matter, and investigation at our data platform .

About the Machine Learning Engineering Role

The Machine Learning Engineer will work with the data scientists and product teams within the AI group to create machine learning solutions at scale. You will help build a machine learning platform to support our team and across the company and ingest and train on real-time and batch data at petabyte scale. Within the AI group you will help train the next batch of ML engineers and provide an organization-wide lift. You'll enjoy your time doing hands-on creation, but also love empowering others through mentorship and coaching.

Your Role in Action

• Work with our data scientists, product managers, and engineering teams to bring ideas from proof of concept to scaled solution.
• Manage and facilitate design decisions related to bringing machine learning algorithms to production using best practices in the industry.
• Prove out the use of new technology with compelling proof of concepts and demonstration.
• Run machine learning tests and experiments
• Contribute to our technical investments roadmap and help prioritize tech debt and architecture investments.
• Mentor talent within the AI group to promote career development.

Your Skills

• Experience supporting the lifecycle of machine learning application from development to production including testing and monitoring those models pre and post-launch.
• Experience training and deploying machine learning models
• Experience working with data science teams with conceptual knowledge on data science project lifecycles and techniques.
• Experience designing APIs, service-oriented architectures, cloud-based distributed systems, and big data systems.
• Fluent in programming languages suitable to implement big data and machine learning solutions. Ex: Python, Scala.
• Experience with product / tool / vendor evaluation and selection.