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.
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:
- 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:
- Drive adoption of MLOps best practices: reproducibility, lineage, rollback, monitoring and governance.
- Mentor junior engineers and influence the broader cloud platform organization’s roadmap.
What We’re Aiming For (MLOps Level 2)
- Version-controlled ML pipelines (data, code, and config)
- Automated and reproducible model training and evaluation
- Continuous integration and delivery for ML workflows
- Centralized experiment tracking and performance visualization
- Standardized model packaging and deployment to production
- Monitoring of models post-deployment
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.
- Experience with robotics, autonomous vehicles, drones or embedded ML.
- 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.
Benefits
- 401(k) Plan: Includes a 6% company match.
- Equity: Company stock options.
- Insurance Coverage: 100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.
- Benefit Start Date: Eligible for benefits on your first day of employment.
- Well-Being Support: Employee Assistance Program (EAP).
- Time Off:
- Exempt Employees: Flexible, unlimited PTO and 10 company holidays, including a winter shutdown.
- Non-Exempt Employees: 10 vacation days, paid sick leave, and 10 company holidays, including a winter shutdown, annually.
- On-Site Perks: Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.
- Parental Leave: Generous paid parental leave programs.
- Work Environment: A culture that supports flexible work arrangements.
- Growth Opportunities: Professional development and tuition reimbursement programs.
- Relocation Assistance: Provided for eligible roles.
Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment.
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/b444bbd04us
Top Skills
Similar Jobs
What you need to know about the Colorado Tech Scene
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
