Senior DevOps Engineer, ML Infrastructure

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.

The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

As a Senior DevOps Engineer on the Machine Learning (ML) Infrastructure team, you will help design, build, and maintain our petabyte-scale data and ML platform that powers data partnerships, ML research, and autonomy engineering. You will play a key role in ensuring reliability, security, scalability, and performance across our internal systems, and maintain a suite of internal tools used by dozens of engineers. Your work will make a significant impact on our autonomous capabilities and act as a catalyst for the entire autonomy team, helping us train our next generation of ML models.

Responsibilities

• Deploy and maintain our ML training orchestration system that operates across multiple platforms.
• Manage cloud and on-premise environments for large-scale distributed data processing and ml training / inference systems.
• Automate deployment pipelines, monitoring, and alerting for ML and data services.
• Collaborate closely with data scientists, ML engineers, and autonomy teams to streamline experimentation and model deployment.
• Maintain and improve CI / CD systems to support rapid development and testing.
• Implement best practices for system security, reliability, and observability.
• Optimize infrastructure costs and ensure efficient resource utilization.
• Support internal developer productivity through tooling, documentation, and support.

Qualifications

What Makes You Stand Out

Canada - Base salary range (Canada - all locations) : $130k - 160k CAD

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