Senior Software Engineer, AI/ML Platform

Agility Robotics•Pittsburgh, PA

2d•$197,000 - $307,000•Remote

About The Position

Agility Robotics is hiring a Senior Software Engineer to help build the machine learning platform that powers its fleet-scale humanoid robotics. As a senior engineer on the ML Infrastructure and Platform group, you will architect and develop foundational infrastructure for AI and machine learning operations, including data collection and processing, training, simulation and real-world evaluation, and model management and observability. Your work will provide AI teams across perception, controls, skills, and innovation with tools to develop and operationalize robot foundation models and end-to-end policies at scale. The role involves implementing reliable workflows across cloud compute, Kubernetes, and continuous automation; developing core platform components and developer-facing APIs and CLI tools; and enabling the ML CI/CD lifecycle, from continuous retraining and automated testing to production model delivery. You will work closely with the Staff ML Infra Engineer, AI researchers, robotics engineers, and data platform engineers. You will also apply MLOps best practices, contribute to architecture and reliability discussions, mentor junior engineers, and influence the broader cloud platform roadmap. Agility Robotics builds commercially deployed humanoid robots that work alongside people in warehouses, manufacturing facilities, and distribution centers. The company describes this as a remote-friendly role on a fully distributed team, with flexible work arrangements. All roles are U.S.-based, and applicants must be authorized to work in the United States.

Requirements

At least 5 years of software engineering experience, including at least 2 years working on ML infrastructure, data platforms, or MLOps systems in production environments.
Experience building and maintaining components of modern ML platforms, such as experiment tracking, model registries, training pipelines, or deployment systems.
Familiarity with orchestration and tracking tools such as MLflow, WandB, Airflow, or Kubeflow.
Proficiency with cloud-native platforms such as AWS, GCP, or Azure, containers, and infrastructure as code such as CDK or Terraform.
Hands-on experience processing or modeling multimodal data, such as sensor logs, camera streams, or behavior traces.
Ability to collaborate cross-functionally with research scientists, data engineers, and robotics or autonomy teams to ship infrastructure used by others.
Current authorization to work in the United States.

Nice To Haves

Experience with robotics, autonomous vehicles, drones, or embedded ML.
Contributions to open-source ML infrastructure or MLOps tooling.

Responsibilities

Contribute to the design and implementation of the ML platform for orchestrating the end-to-end AI flywheel of data processing, training, evaluation, and deployment.
Develop reliable workflows across cloud compute, Kubernetes, and continuous automation.
Build core infrastructure components such as the model registry, feature store, and experiment-tracking tooling.
Own developer-facing APIs and CLI tools that make ML workflows simple and reproducible.
Implement the CI/CD lifecycle for ML, enabling continuous retraining, automated testing, and seamless model delivery to production environments.
Work with the Staff ML Infra Engineer and cross-functional stakeholders, including AI researchers and robotics engineers, to understand requirements and translate them into scalable solutions.
Partner with data platform engineers to integrate ML orchestration and metadata-tracking tools with existing data lakes and pipelines.
Apply MLOps best practices, including reproducibility, lineage, rollback, monitoring, and governance.
Mentor junior engineers and influence the broader cloud platform organization's roadmap.
Contribute to internal discussions on platform architecture, reliability, and scalability with the ML and data platform team.

Benefits

401(k) plan with a 6% company match.
Company stock options.
100% company-paid medical, dental, and vision insurance for employees.
100% company-paid short- and long-term disability insurance for employees.
Benefits eligibility begins on the first day of employment.
Employee Assistance Program (EAP).
Flexible, unlimited PTO and 12 company holidays, including a winter shutdown, for exempt employees.
For non-exempt employees: 10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually.
Catered lunches four times a week and healthy snacks and refreshments at Salem and Pittsburgh locations.
Paid parental leave programs.
Flexible work arrangements.
Professional development and tuition reimbursement programs.
Relocation assistance for eligible roles.
Annual discretionary bonus for eligible roles.