Machine Learning Engineer – Cloud | MLOps | GenAI (Relocation provided)
Tasks
- Automate and monitor ML workflows using MLflow Airflow or cloud-native tools
- Collaborate with data scientists, engineers, and product teams
- Contribute to MLOps practices such as model versioning CI/CD performance monitoring rollback
- Design and implement machine learning pipelines in cloud environments
- Develop and deploy models for classification regression time series recommendation NLP use cases
- Package and deploy models using containerization
- Work with structured and unstructured data and apply feature engineering model tuning evaluation techniques
Perks/Benefits
- 24 days paid vacation
- Flexible work environment
- Permanent contract
- Professional development budget
- Relocation support
- Team events
- Travel reimbursement
- Visa sponsorship
Skills/Tech-stack
APIs | AWS | Airflow | Azure | DVC | Data Lakes | Distributed Systems | Docker | Ethical ML | Explainability | Feast | GCP | HuggingFace Transformers | Kubernetes | Langchain | MLflow | PyTorch | Python | RAG | Responsible AI | SageMaker | Sklearn | Tecton | TensorFlow | Vertex AI | XGBoost
Education
N/A
Regions
Countries
States
Cities
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