AI/ML Engineer – GenAI & MLOps (on-site)
EUR 45K-60K (estimate) Mid-level Full Time
Tasks
- Apply MLOps principles including model versioning and deployment
- Build feature engineering pipelines
- Collect clean transform and document structured and unstructured data
- Communicate results to non-technical stakeholders
- Define AI project goals and success metrics
- Develop and apply generative AI solutions using LLM RAG and prompt engineering
- Develop, train, evaluate, and optimize machine learning models
- Document models and components
- Expose AI solutions via REST APIs
- Implement automation and orchestration for batch and real time workflows
- Manage model quality and risk
- Monitor model performance in production
- Translate business requirements into technical specifications
Perks/Benefits
Skills/Tech-stack
AI Governance | AWS | Agile | Apache Airflow | Automation | Azure | Bias Management | Chroma | Data Preparation | Feature Engineering | GCP | GenAIOps | Generative AI | Kubeflow | LLM | Langchain | Llamaindex | MLOps | MLflow | Machine Learning | Model Monitoring | Model versioning | Orchestration | Pinecone | Prefect | Prompt engineering | Python | RAG | REST API | Vector Databases | Weaviate | Weights and Biases | XAI
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | ML Engineer | MLOps Engineer
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