Senior MLOps Engineer - Edge AI, Remote Deployment

Hudl; España; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Flexible vacation time

Remote work options

Company holidays and timeout days

Job summary

You’ll work with Data Scientists, Embedded Engineers, and Product Managers to ensure reliable, scalable deployment, canaries, and telemetries, while mentoring the team on Python tooling and IaC best practices.

Qualifications

• Production MLOps pipelines deployed to production environments.
• Experience with edge devices deployment and model compilation.
• Collaboration with data scientists and embedded engineers.
• Ability to design robust, scalable edge architectures.

Responsibilities

• Build scalable Edge infrastructure and deployment systems for fleets of devices.
• Own the model compilation pipeline to produce optimized inference engines.
• Work with cross-functional teams to integrate features.
• Drive automation and telemetry for model drift and latency.

Skills

Edge inference

TensorRT

Python tooling

CI/CD

Docker

Kubernetes

IaC

Linux systems

Canary releases

Tools

Docker

Kubernetes

TensorRT

Jetson Orin

GStreamer

Balena

AWS IoT Greengrass

Job description

You’ll work with Data Scientists, Embedded Engineers, and Product Managers to ensure reliable, scalable deployment, canaries, and telemetries, while mentoring the team on Python tooling and IaC best practices.