AI Engineer
Tasks
- Build production APIs and microservices
- Define MVP scope and success metrics
- Design MLOps pipelines for training and deployment
- Develop and deploy large language model solutions
- Develop and deploy machine learning models
- Develop user interfaces and dashboards
- Engineer feature pipelines and transformations
- Ensure responsible AI governance
- Implement CI/CD for model deployments
- Implement model monitoring and drift detection
- Integrate AI into enterprise systems
- Perform exploratory data analysis
- Translate business needs into AI products
Perks/Benefits
- Consultations
- Employee events
- Extra vacation days
- Flexible benefits allowance
- Flexible working hours
- Home office
- Housing allowance
- Language courses
- Meal card contribution
- Medical examinations
- Private canteen
- Regular onsite exercises
- Relocation package
- Team building events
- Volunteering opportunities
- Workplace massages
Skills/Tech-stack
Apache Spark | Azure | CI/CD | Compliance | Data Contracts | Deep learning | Docker | Drift Detection | Explainability | Fairness | FastAPI | Feature Engineering | Flask | LLM | MLOps | Machine Learning | Microservices | Model Monitoring | Model versioning | Power BI | Privacy | Prompt engineering | PyTorch | Python | React | Retrieval-Augmented Generation | Scikit-learn | Snowflake | Streamlit | TensorFlow
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
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