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ML Ops / Data Engineer - Robotics(m/w/x)
Building multi-sensor telemetry pipelines and ML Ops for autonomous heavy machinery at robotics platform. 3+ years building cloud data pipelines with Python/SQL proficiency required. Stock options, engagement with top-tier researchers.
Requirements
- 3+ years experience building cloud data pipelines
- Proficiency in Python, SQL, and big-data frameworks
- Familiarity with ML Ops tooling
- Experience designing data warehouses or data lakes
- Understanding of distributed systems and data serialization
- Excellent problem-solving skills and adaptability
- Background in robotics or sensor data
- Knowledge of real-time data processing
- Experience with infrastructure as code and CI/CD
- Familiarity with Kubernetes and containerized deployments
- Exposure to vision-language or action-planning models
Tasks
- Design and maintain data infrastructure
- Build and operate multi-sensor telemetry pipelines
- Architect scalable data lakes and warehouses
- Integrate ML Ops tools like DVC or MLflow
- Automate model training and retraining triggers
- Track data and model lineage
- Implement data validation and monitoring systems
- Collaborate on data schemas and APIs
- Optimize distributed processing and storage performance
- Document pipeline architectures and ML Ops practices
Education
- Vocational certificationOR
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- AWS
- GCP
- Azure
- Python
- SQL
- DVC
- MLflow
- Kubeflow
- Redshift
- Snowflake
- BigQuery
- Delta Lake
- Parquet
- Avro
- Terraform
- CloudFormation
- Kubernetes
Benefits
Competitive Pay
- Attractive compensation package
- Stock options
Snacks & Drinks
- On-site beverages
Team Events
- Regular social events
Other Benefits
- Engagement with top-tier researchers
- Influence future robotic technologies
Additional Allowances
- Relocation assistance to Berlin
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ML Ops / Data Engineer - Robotics(m/w/x)
Building multi-sensor telemetry pipelines and ML Ops for autonomous heavy machinery at robotics platform. 3+ years building cloud data pipelines with Python/SQL proficiency required. Stock options, engagement with top-tier researchers.
Requirements
- 3+ years experience building cloud data pipelines
- Proficiency in Python, SQL, and big-data frameworks
- Familiarity with ML Ops tooling
- Experience designing data warehouses or data lakes
- Understanding of distributed systems and data serialization
- Excellent problem-solving skills and adaptability
- Background in robotics or sensor data
- Knowledge of real-time data processing
- Experience with infrastructure as code and CI/CD
- Familiarity with Kubernetes and containerized deployments
- Exposure to vision-language or action-planning models
Tasks
- Design and maintain data infrastructure
- Build and operate multi-sensor telemetry pipelines
- Architect scalable data lakes and warehouses
- Integrate ML Ops tools like DVC or MLflow
- Automate model training and retraining triggers
- Track data and model lineage
- Implement data validation and monitoring systems
- Collaborate on data schemas and APIs
- Optimize distributed processing and storage performance
- Document pipeline architectures and ML Ops practices
Education
- Vocational certificationOR
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- AWS
- GCP
- Azure
- Python
- SQL
- DVC
- MLflow
- Kubeflow
- Redshift
- Snowflake
- BigQuery
- Delta Lake
- Parquet
- Avro
- Terraform
- CloudFormation
- Kubernetes
Benefits
Competitive Pay
- Attractive compensation package
- Stock options
Snacks & Drinks
- On-site beverages
Team Events
- Regular social events
Other Benefits
- Engagement with top-tier researchers
- Influence future robotic technologies
Additional Allowances
- Relocation assistance to Berlin
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
sensmore
Industry
Manufacturing
Description
The company automates the world's largest machines with unprecedented intelligence, integrating robotics into a platform for productivity and safety.
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