Qualifications

• BS/MS in Computer Science, Electrical Engineering, or similar field; equivalent experience acceptable.
• 3+ years in platform, ML infrastructure, or backend/distributed systems.
• Proficiency with containers and orchestration tools like Docker and Kubernetes.
• Strong programming skills in Python and/or Go, particularly in data pipelines and deployment.
• Knowledge of edge hardware (e.g., NVIDIA Jetson) and real-time systems is advantageous.
• Ability to collaborate between software engineering and production environments.
• Bilingual skills in English and Spanish are a bonus.

Responsibilities

• Build and manage the platform for deploying and updating vision models on edge nodes.
• Oversee fleet management, including device health, model versioning, and over-the-air updates.
• Develop the data platform to create pipelines from cameras and machines to storage for defect tracking.
• Monitor system observability including latency, accuracy, uptime, and drift across the network.
• Containerize and orchestrate workloads to ensure 24/7 uptime at scale.
• Collaborate with computer vision/machine learning teams and production quality controls to improve operations.

Benefits

• Opportunity to work at the intersection of cutting-edge technology and practical applications.
• Collaborative work environment with interdisciplinary teams.
• Hands-on experience with state-of-the-art machine learning and robotics hardware.
• Engagement in a role that has a direct impact on operational efficiencies.
• Potential for professional growth in a rapidly evolving tech landscape.