Machine Learning Engineer

01 ago - Italia
Mynameis

The company
Our client is a leading company in the field of cognitive humanoid robotics based in Monza Brianza and founded in 2020, focused on developing cognitive humanoid robotics for progress and well-being.
The mission is to make the benefits of the future accessible by creating innovative solutions for industry and healthcare. The aim is about to support people in repetitive, dangerous, and strenuous jobs with technological solutions that integrate with daily life and respect the environment.
We are looking for a Machine Learning Engineer (Mid/Senior) to work on ML infrastructure and production pipelines for Physical AI and robotics systems.

The role is focused on:
- ML pipeline orchestration
- training/inference workflows
- model deployment
- data processing for sensor and telemetry streams
- MLOps and infrastructure automation

The position is engineering-oriented and production-focused with at least 2 years of experience to join the Carate Brianza headquarters.

Responsibilities
- Build and maintain ML pipelines for robotics and Physical AI applications
- Manage training, evaluation,



deployment, and monitoring workflows
- Develop data and feature pipelines for sensor and time-series data
- Work on edge/cloud ML integration
- Improve reliability and observability of ML systems
- Containerize and deploy ML services
- Collaborate with robotics, cloud, and data teams
- Support predictive maintenance and anomaly detection pipelines

Requirements

Must-have
- Strong Python skills
- Experience deploying ML systems in production
- Experience with Docker and Kubernetes
- Experience with ML pipelines and MLOps workflows
- Familiarity with CI/CD and infrastructure automation
- Linux and Git
- Experience handling real-world noisy datasets

Nice-to-have
- PostgreSQL / TimescaleDB
- Kafka or streaming systems
- Robotics or IoT systems
- Time-series data
- Edge AI deployments
- GPU workloads
- Monitoring/observability tooling

Location - Carate Brianza (MB)
Budget between

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