Accenture
DevOps Engineer(m/w/x)
Full-time/Part-timeOn-siteExperienced
Zürich
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GRGravis Robotics
Data & ML Ops Engineer(m/w/x)
Zürich
Part-time, Full-timeOn-siteExperienced
AI/ML
Data Science
Nejo AI Summary
Designing and operating end-to-end ML pipelines for autonomous construction robots. 3+ years of ML Ops or ML infrastructure experience required. Flexible hybrid work, 4-day work week.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Engineering, Electrical Engineering, or related field
- 3+ years of ML Ops, data engineering, or ML infrastructure experience
- Strong Python skills
- Solid experience with ML frameworks (PyTorch or TensorFlow)
- Proven experience building and managing CI/CD pipelines for ML workloads
- Hands-on containerization experience (Docker)
- Experience with cloud platforms (AWS, GCP, or Azure)
- Experience with data versioning, experiment tracking, and workload orchestration tools
- Experience with GPU accelerated simulation environments
- Experience working with robotics data (point clouds, camera streams, timeseries data)
- Hands-on infrastructure as code experience
- Experience with Robotics & DevOps related tooling
- Experience scaling ML infrastructure
- Proficiency in English
Tasks
- Design and operate end-to-end ML pipelines
- Ingest and preprocess multimodal robotics data
- Version and manage training data
- Train and evaluate ML models
- Deploy models to edge devices and cloud infrastructure
- Build and maintain scalable data platform
- Manage CI/CD pipelines for ML workflows
- Automate model training and regression testing
- Deploy models to production fleets
- Track experiments and manage model registry
- Ensure artifact versioning for reproducibility
- Collaborate with Autonomy and Perception engineers
- Translate requirements into scalable training environments
- Evaluate and integrate MLOps tools
- Support cloud and on-prem compute platforms
Work Experience
- 3 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Native
Tools & Technologies
- Python
- PyTorch
- TensorFlow
- GitHub Actions
- GitLab CI
- Docker
- AWS
- GCP
- Azure
- MLflow
- W&B
- clear.ml
- DVC
- IsaacSim/IsaacLab
- CARLA
- MuJoCo
- Foxglove
- Prometheus
- Grafana
Benefits
Flexible Working
- Work-life balance
- Flexibility
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Gravis Robotics and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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GRGravis Robotics
Data & ML Ops Engineer(m/w/x)
Zürich
Part-time, Full-timeOn-siteExperienced
AI/ML
Data Science
Nejo AI Summary
Designing and operating end-to-end ML pipelines for autonomous construction robots. 3+ years of ML Ops or ML infrastructure experience required. Flexible hybrid work, 4-day work week.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Engineering, Electrical Engineering, or related field
- 3+ years of ML Ops, data engineering, or ML infrastructure experience
- Strong Python skills
- Solid experience with ML frameworks (PyTorch or TensorFlow)
- Proven experience building and managing CI/CD pipelines for ML workloads
- Hands-on containerization experience (Docker)
- Experience with cloud platforms (AWS, GCP, or Azure)
- Experience with data versioning, experiment tracking, and workload orchestration tools
- Experience with GPU accelerated simulation environments
- Experience working with robotics data (point clouds, camera streams, timeseries data)
- Hands-on infrastructure as code experience
- Experience with Robotics & DevOps related tooling
- Experience scaling ML infrastructure
- Proficiency in English
Tasks
- Design and operate end-to-end ML pipelines
- Ingest and preprocess multimodal robotics data
- Version and manage training data
- Train and evaluate ML models
- Deploy models to edge devices and cloud infrastructure
- Build and maintain scalable data platform
- Manage CI/CD pipelines for ML workflows
- Automate model training and regression testing
- Deploy models to production fleets
- Track experiments and manage model registry
- Ensure artifact versioning for reproducibility
- Collaborate with Autonomy and Perception engineers
- Translate requirements into scalable training environments
- Evaluate and integrate MLOps tools
- Support cloud and on-prem compute platforms
Work Experience
- 3 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Native
Tools & Technologies
- Python
- PyTorch
- TensorFlow
- GitHub Actions
- GitLab CI
- Docker
- AWS
- GCP
- Azure
- MLflow
- W&B
- clear.ml
- DVC
- IsaacSim/IsaacLab
- CARLA
- MuJoCo
- Foxglove
- Prometheus
- Grafana
Benefits
Flexible Working
- Work-life balance
- Flexibility
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Gravis Robotics and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Gravis Robotics
Industry
Construction
Description
Gravis Robotics is a startup that turns heavy construction machines into intelligent and autonomous robots.
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