Agility Robotics is a pioneer. Our robot, Digit, is the first to be sold into workplaces across the globe. Our team is differentiated by its expertise in imagining, engineering, and delivering robots with advanced mobility, dexterity, intelligence, and efficiency - robots specifically designed to work alongside people, in spaces built for people. Every day, we break through engineering challenges and invent new solutions and capabilities that will one day make robots commonplace and approachable. This work is our passion and our responsibility: our mission is to make businesses more productive and people’s lives more fulfilling.

REQUIRED QUALIFICATIONS

• 8+ years of software engineering experience or ML infrastructure experience with a demonstrated track record of building data platforms and MLOps pipelines.
• Expertise in modern data platform technologies.
• Significant experience with ML frameworks and orchestration tools (MLflow, WandB, Airflow, Kubeflow, etc.)
• Strong proficiency with cloud-native tooling (AWS, GCP, or Azure), containers, and IaC (e.g., CDK, Terraform)
• Experience working cross-functionally with ML, data, and platform teams.

BONUS QUALIFICATIONS

• Experience with robotics, autonomous vehicles, drones or embedded ML.

AGILITY ROBOTICS DOES NOT ACCEPT UNSOLICITED REFERRALS FROM THIRD-PARTY RECRUITING AGENCIES. WE PRIORITIZE DIRECT APPLICANTS AND ENCOURAGE ALL QUALIFIED CANDIDATES TO APPLY DIRECTLY THROUGH OUR CAREERS PAGE. IF YOU ARE REPRESENTED BY A THIRD PARTY, YOUR APPLICATION MAY NOT BE CONSIDERED. TO ENSURE FULL CONSIDERATION, PLEASE APPLY DIRECTLY.

Apply Now: https://grnh.se/b444bbd04u

ABOUT THE ROLE

Join the cutting-edge team building the data and machine learning infrastructure to power fleet-scale humanoid robotics. As the lead engineer on the ML Infrastructure group on the Data Platform team, you will architect and build the foundational infrastructure for AI and machine learning operations at Agility. You will be the first dedicated ML Infrastructure hire, responsible for designing and building the ML layer on top of our core data platform. Your work will empower our perception, planning and autonomy teams with tools to develop and operationalize machine learning at scale.

KEY RESPONSIBILITIES

• Vision: You will define a long-term vision for ML infra aligning it with company goals and industry best practices
• Strategy: You will deliver a road map for the development of a level 2 MLOps platform after consulting with AI researchers on our innovation team, perception engineers and other stakeholders in the robotics organization.
• Collaboration: You will partner with data platform engineers to set up and integrate ML workflow orchestration and tracking systems with existing data platform tooling.
• Execution:
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• You will design and implement our ML development environment including a secure, scalable workspace for interactive experimentation(JupyterHub etc)

• Develop core infrastructure including a model registry, feature store and experiment tracking tooling.
• Define the CI/CD lifecycle for ML that enable continuous retraining, automated testing, and seamless model delivery to production environments
• Leadership:
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• Drive adoption of MLOps best practices: reproducibility, lineage, rollback, monitoring and governance.

• Mentor junior engineers and influence the broader cloud platform organization’s roadmap.

WHY THIS ROLE?

• Greenfield/Zero-to-One: You’ll lead and define the company-wide ML infrastructure layer from the ground up
• High impact: Your work will directly enable faster, safer, and more intelligent robotic behaviors at scale
• Remote-friendly with a strong engineering culture and a fully distributed team.