Senior ML Platform Engineer – Scale AI for Humanoid Robotics

Precision Labs; United States; Hybrid; USD 197,000 - 307,000; Full time

Benefits offered by this job

401(k) Plan with match

Stock options

Full healthcare coverage

Unlimited PTO and holidays

Relocation assistance

Annual discretionary bonus

Tuition reimbursement

Job summary

Agility Robotics is seeking a senior ML Infrastructure and Platform engineer to build the foundation for AI operations at scale. You’ll design the data, training, sim/evaluation, and model management layers to empower robotics teams.

Take ownership of the ML platform, APIs, and CI/CD while collaborating with researchers and engineers to deploy robust, scalable solutions across perception, controls, and robotics workflows.

Qualifications

• 5+ years of software engineering with 2+ years in ML infrastructure
• Experience building ML platforms: training pipelines, model deployment
• Familiarity with orchestration and tracking tools (MLflow, WandB, Airflow, Kubeflow)
• Proficiency with cloud platforms (AWS/GCP/Azure) and IaC
• Hands-on experience with multimodal data

Responsibilities

• Design and implement ML platform for end-to-end AI flywheel
• Develop workflows across cloud, Kubernetes, and CI/CD
• Build core components: model registry, feature store, experiment tracking
• Own APIs and CLI for ML workflows
• Implement CI/CD for ML with retraining and model delivery
• Collaborate with researchers and engineers
• Integrate ML orchestration with data lake pipelines
• Apply MLOps: reproducibility, lineage, monitoring
• Mentor junior engineers
• Contribute to platform architecture discussions

Skills

ML infrastructure

ML platforms

Cloud-native platforms

IaC (CDK/Terraform)

Kubernetes

Experiment tracking

Model registry

Tools

MLflow

WandB

Airflow

Kubeflow

AWS

GCP

Terraform

CDK

Job description

Agility Robotics is seeking a senior ML Infrastructure and Platform engineer to build the foundation for AI operations at scale. You’ll design the data, training, sim/evaluation, and model management layers to empower robotics teams.

Take ownership of the ML platform, APIs, and CI/CD while collaborating with researchers and engineers to deploy robust, scalable solutions across perception, controls, and robotics workflows.