Robotics MLOps & Data Engineer (f/m/d)

Hexagon Robotics; Zürich; Hybrid; CHF 120.000 - 180.000; Vollzeit

Benefits dieser Stelle

Mobility credit

Relocation support

Pension contributions

Training opportunities

Team events

Zusammenfassung

Hexagon Robotics in Zürich, Switzerland, is seeking a Robotics MLOps & Data Engineer to architect and implement production-grade MLOps and data infrastructure for our humanoid robotics program. You will design scalable pipelines for training, evaluation and deployment of ML models across R&D teams and ensure robust tooling and governance.

Responsibilities include creating templates, driving CI/CD for data and ML pipelines, collaborating with robotics teams, and promoting best practices for

Qualifikationen

• MSc/PhD in CS with focus on machine learning.
• Strong MLOps and data infrastructure knowledge.
• Proven production-grade MLOps experience.
• Experience with CI/CD, IaC, and containerization.
• English proficiency; German helpful.

Aufgaben

• Architect and implement production‑grade MLOps/data infrastructure enabling R&D to deploy ML solutions for robotics.
• Advance data ingestion, storage and sharing for high‑value robotics datasets.
• Design scalable pipelines to ingest, process and store real-world and simulated datasets.
• Create scalable ML pipelines to train, evaluate and deploy models for robotics.
• Write templates, document tooling, and mentor R&D teams on MLOps capabilities.
• Promote CI/CD best practices for data/ML pipelines with versioning and testability.
• Collaborate with robotics teams to translate requirements into robust infrastructure.

Kenntnisse

MLOps

Data infrastructure

Python

CI/CD

Terraform

Docker

Kubernetes

Azure Data Lake

Azure ML

MLflow

PyTorch

TensorFlow

JAX

ROS2

Omniverse

English

Agile mindset

Ausbildung

MSc/PhD in Computer Science or equivalent

Tools

Azure Data Lake

Azure ML

MLflow

Terraform

Docker

Kubernetes

ROS2

Omniverse

PyTorch

TensorFlow

Jobbeschreibung

Hexagon Robotics is a division of Hexagon – a global leader in precision measurement. The division develops humanoid robots for industrial sectors to address labor shortages and accelerate the transition from automation to autonomy. Our first humanoid, AEON, was launched in June 2025 and is already in pilots with five customers.

We are looking for a Robotics MLOps & Data Engineer to architect and implement production-grade MLOps and data infrastructure and core capabilities that enable R&D teams across Hexagon to develop and deploy cutting‑edge machine learning solutions for humanoid robotics. The role further involves designing and developing scalable and reproducible data and ML pipelines for the training, evaluation and deployment of ML models, and working with R&D teams to facilitate the adoption of the capabilities and tooling of state‑of‑the‑art MLOps / data infrastructure.

Your Mission

• Architect and implement production‑grade MLOps / data infrastructure and core capabilities that enable R&D teams across Hexagon to develop and deploy cutting‑edge machine learning solutions for robotics
• Advance the strategy and standards for data ingestion, storage, management and sharing to enable the creation and usage of high‑value robotics datasets
• Design and develop scalable data pipelines to ingest, process and store both real‑world and simulated robotics datasets, and facilitate data sharing and usage
• Design and develop scalable and reproducible ML pipelines to train, evaluate and deploy ML models for robotics
• Create pipeline templates and work with R&D teams to facilitate the adoption and use of MLOps / data infrastructure and tooling, write clear documentation, provide hands‑on guidance and share knowledge
• Establish and promote engineering and CI/CD best practices for data and ML pipelines, ensuring versioning, modularity, testability and high‑quality releases
• Work closely with R&D teams to understand their requirements, translating needs into high‑quality and effective infrastructure and tooling

Your Skillset

• MSc/PhD in Computer Science or equivalent with a focus on machine learning
• Deep understanding of MLOps and data infrastructure concepts and tooling, including the data and ML lifecycle, considering both functional and non‑functional requirements
• Proven track record in implementing and operating production‑grade MLOps and data infrastructure, with capabilities for data storage and processing, ML experimentation, data and ML pipelines, tracking, registering and deployment of ML models
• Solid experience in implementing modular, testable and scalable data and ML pipelines
• Hands‑on experience with cloud, hybrid and on‑premises environments. Experience with Azure data and ML services, such as Azure Data Lake, Azure ML is a plus
• Proficiency in ML frameworks, e.g. PyTorch, TensorFlow, or JAX, and tooling, e.g. MLflow
• Solid software engineering skills in Python, ability to write clean, testable and maintainable production‑ready code, experience with CI/CD, IaC (Terraform), containerization (Docker) and container orchestration (Kubernetes)
• Experience in ML models for robotics and in deploying ML‑based models to robotic hardware is a plus. Knowledge of robotics frameworks and tools (particularly ROS2, Omniverse) and the ability to work closely with robotics teams is a plus
• Ability to assess and select third‑party frameworks and tooling with long‑term operational and maintenance considerations in mind
• Strong agile mindset, ability to operate with autonomy, strong communication skills, ability to work in a customer‑oriented way with technical and non‑technical stakeholders, ability to enable teams
• Proficiency in English required, basic German skills advantageous

What You’ll Get

• Flexible working hours and a hybrid model for real work‑life balance
• CHF 500 mobility credit for sustainable commuting
• Bonus system & strong pension contributions
• Tailored training & development opportunities
• Relocation support for a smooth start
• Discounts on health, mobility & entertainment
• Team events and a flat hierarchy where your voice counts
• A warm, international culture built on respect and collaboration