AI Engineer
Tasks
- Apply responsible AI bias monitoring and explainability
- Build maintain large language model applications
- Build retrieval-augmented generation pipelines
- Design develop deploy AI/ML solutions
- Develop intelligent agents and orchestration
- Develop scalable backend services and API layers
- Implement AI safety guardrails and governance controls
- Implement cloud native AI ML pipelines
- Monitor evaluate and validate AI models
- Perform proofs of concept and rapid prototyping
- Set up MLOps and LLMOps workflows
Perks/Benefits
- N/A
Skills/Tech-stack
API Development | AWS | Agent Orchestration | Apache Spark | Artificial Intelligence | Azure Data | Azure Data Services | Azure OpenAI | CI/CD | Cloud Computing | Data Pipelines | Data Services | Databricks | Databricks Lakehouse | Explainability | Fairness | Generative AI | Google Gemini | Hugging Face | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Microservices | Microsoft Azure | Microsoft Fabric | Model Deployment | Model Governance | Model Monitoring | OpenAI | Prompt engineering | PyTorch | Python | Responsible AI | Retrieval-Augmented Generation | SQL | Semantic Search | TensorFlow | Vector embeddings
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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