Senior Platform Engineer

Position Overview

The ARM Institute is a national public-private partnership dedicated to accelerating the adoption of robotics and artificial intelligence (AI) in U.S. manufacturing, strengthening national competitiveness and security. Based in Pittsburgh, Pennsylvania and sponsored by the Department of Defense (DoD), this institute is a key component of the Manufacturing USA network.

We’re a small, collaborative team seeking a Senior Platform Engineer to own and operate the data, machine learning, and deployment infrastructure powering next-generation robotics R&D. In this role you’ll build and maintain open-source tooling for data pipelines, model development, automated deployment, and scalable compute—while supporting manufacturers as they adopt and integrate the platform. This is a hybrid role (3 days in office, 2 days remote) based in our Pittsburgh office.

Key Responsibilities

• Build and maintain data pipelines, storage, and ingestion workflows for robotics datasets.
• Develop and operate an end-to-end MLOps platform including experiment tracking, model registry, packaging, training/evaluation automation, and deployment.
• Own CI/CD and automation using GitHub Actions, Ansible, and containerized development environments.
• Help maintain a library of curated Docker containers and base images following industry best practices for security and performance.
• Implement telemetry/monitoring stacks for remote debugging and system health.
• Collaborate with robotics engineers, data scientists, and industry partners to integrate and transfer platform components.

Required Qualifications

• Bachelor’s degree in computer science, engineering, or a related technical field.
• Minimum of 5 years of experience in DevOps, MLOps, platform engineering, or data engineering.
• Strong experience with Docker and development containers, GitHub Actions, and Linux debugging.
• Hands-on experience with Ansible or similar automation tools.
• Experience using MLflow, ClearML, Weights & Biases (W&B), or comparable MLOps frameworks.
• Familiarity with monitoring and observability tools such as Grafana, Prometheus, OpenTelemetry (OTel), or similar stacks.
• Experience managing cloud and on-premises compute and storage and building reliable distributed services.
• Comfortable performing light physical activity and using standard office equipment.
• Willingness and ability to travel up to 20%.

Preferred Qualifications

• Master’s degree in a relevant field.
• Experience with robotics or industrial automation.
• Contributions to open-source projects.