Data scientist and AI engineer
Tasks
- Define and implement model quality and lifecycle strategies
- Design and operate end-to-end ML pipelines
- Design develop and validate data-driven models and AI solutions
- Develop train evaluate and deploy machine learning and AI models
- Explore analyze and transform complex data
- Industrialize AI solutions for manufacturing and engineering environments
Perks/Benefits
- Cafeteria allowance
- Career Development Programs
- Childcare support
- Commute cost coverage
- Extra holiday
- Family support benefits
- Financial security and recognition
- Flexible working hours
- Health care
- International assignment opportunities
- Loyalty jubilees
- Mentoring and coaching
- Mobility services
- Onsite canteen
- Onsite medical center
- Recreation facilities
- Regular health checkups
- Sabbatical
- Training and professional development
- Work from home options
Skills/Tech-stack
Azure | CI/CD | Data Lakes | Data Versioning | Databricks | Docker | Feature Engineering | GitHub Actions | Java | Kafka | MLOps | Pipeline Orchestration | PyTorch | Python | Scala | Scikit-learn | Spark | TensorFlow
Education
Roles
AI | AI Engineer | Data Scientist | Engineer | Scientist
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