Top Remote Platform Engineer Jobs in Chicago, IL

Seeking a Senior Machine Learning Platform Engineer to join the Machine Learning Foundations team at a company focused on economic empowerment. Responsibilities include building self-service tooling for the model lifecycle, collaborating with internal teams, leading architectural discussions, mentoring teammates, and more.

Develop scoped applications utilizing ServiceNow's platform functionality, create and maintain API integrations, lead integration to new technologies, enforce software engineering best practices, design user-friendly software, contribute to new features, and mentor colleagues.

Seeking a Platform Developer with expertise in Braze to join a dynamic team. Responsibilities include developing solutions for cross-channel campaigns, supporting platform development and execution, providing technical expertise, and optimizing campaign workflows. Preferred qualifications include 5+ years of marketing automation platform experience and 2+ years with Braze.

Seeking a Staff Machine Learning Platform Engineer to build and deploy ML applications, improve processes, and collaborate with various teams. Requires 7+ years of ML Platform/ML Ops experience, proficiency in Python and ML tools, LLM knowledge, infrastructure building experience, and a team player mentality.

The Data Platform team at Kin is responsible for building the data ingestion, processing, and storage infrastructure for various teams within the company to use and understand data. The role requires strong problem-solving skills and the ability to work in an agile environment.

The Cloud Engineer role at Inspira Financial involves designing, administrating, maintaining, and supporting enterprise infrastructure, including private and public clouds, networks, servers, and databases. The role requires close collaboration with development teams and business leaders.

Build infrastructure to handle metadata for hundreds of billions of files, scale Dropbox as the data-fabric connecting hundreds of millions of apps, and optimize the analytics platform to derive meaning from vast amounts of data.

Build deployment mechanisms for innovation and safety in a fast-paced environment. Use technologies like Salt, Go, Postgres, Temporal, Kubernetes, Prometheus, Grafana, and Sentry.