AI/ML Engineer & MLOps 80-100%
Glattpark AmbassadorHouse, Switzerland
CHF 190K-236K (estimate) Senior-level Full Time
Tasks
- Apply security privacy and audit controls
- Build evaluation harnesses for ML and GenAI
- Build reusable ML and GenAI components
- Build training and inference pipelines
- Coach teams on MLOps and LLMops best practices
- Create runbooks and incident response procedures
- Deploy and operate ML and GenAI services
- Design ML and GenAI production solutions
- Develop CI CD workflows for ML and GenAI
- Execute reproducible experimentation
- Implement RAG components
- Implement Responsible-AI guardrails
- Implement feature store patterns
- Implement monitoring for quality drift and latency
- Implement observability for models and services
- Industrialize ML and GenAI prototypes
- Maintain automated retraining triggers
- Manage dataset and feature versioning
- Manage model promotion dev test prod
- Operate model registry and versioning
- Produce model documentation and compliance artifacts
- Set SLOs and SLIs for model services
Perks/Benefits
- N/A
Skills/Tech-stack
Airflow | Alerting | Amazon SageMaker | Automation | Azure DevOps | Azure Machine Learning | Batch Processing | CI/CD | Dagster | Data Versioning | Docker | Drift Detection | Experiment tracking | Feature Store | GRPC | Git | GitHub Actions | GitOps | Kubeflow | Kubernetes | ML pipelines | MLflow | Machine Learning | Model Monitoring | Model Registry | Observability | Prefect | Pulumi | PyTorch | Python | RAG | REST | Responsible AI | SLO SLIs | Scikit-learn | Streaming Data | TensorFlow | Terraform | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Engineer | Engineer | ML Engineer | MLOps Engineer
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