AI Engineer
Tasks
- Build AI solutions on Azure AWS and Google Cloud
- Build generative AI assistants copilots and agents
- Collaborate with engineering and security teams
- Continuously improve AI solutions and knowledge
- Create data pipelines and feature engineering
- Deploy and monitor AI models
- Design AI and machine learning solutions
- Design scalable APIs and microservices
- Develop and implement end to end AI applications
- Develop cloud native AI architectures
- Implement MLOps and LLMOps pipelines
- Implement RAG with vector search
- Integrate AI services with client requirements
Perks/Benefits
- Annual end year bonus
- Bring your own device allowance
- Company car
- Eco vouchers
- Extra vacation options
- Family coverage option
- Flexible income plan
- Flexible work arrangements
- Group insurance
- Health insurance
- Laptop
- Meal vouchers
- Mobile Plan
- Professional development
- Telework options
- Work-life balance
Skills/Tech-stack
AI Foundry | AI Search | API Development | AWS Bedrock | AWS Lambda | Amazon SageMaker | Azure AI | Azure AI Foundry | Azure AI Search | Azure Machine Learning | Azure OpenAI | C# | CI/CD | Deep learning | Docker | Fine Tuning | Generative AI | Git | Google Cloud | Java | JavaScript | Kubernetes | LLMOps | Langchain | Language Models | Large Language Models | Llamaindex | MLOps | Machine Learning | Microservices | Microsoft Azure | Microsoft Fabric | Model Evaluation | Prompt engineering | PyTorch | Python | Responsible AI | Retrieval-Augmented Generation | Scikit-learn | Semantic Kernel | Semantic Search | TensorFlow | Vector Database | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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