AI Engineer
Tasks
- Build Retrieval Augmented Generation systems
- Build machine learning pipelines
- Collaborate with product teams and domain experts
- Deploy LLM solutions into production
- Design LLM solutions
- Develop text representation pipelines
- Evaluate model performance
- Extract semantics from unstructured data
- Implement CI/CD pipelines
- Implement LLM solutions
- Integrate LLM features into SaaS platform
- Monitor ML deployments
- Perform prompt engineering
- Prepare data for ML
- Process and transform data
- Use LLM models with agentic approaches
- Use context engineering techniques
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic AI | Azure | CI/CD | CPU Optimization | Context engineering | Continuous Delivery | Continuous integration | Data Processing | Data extraction | Elasticsearch | GPU Optimization | Grafana | Infrastructure as Code | Language Models | Large Language Models | Machine Learning | Monitoring | Observability | Prometheus | Prompt engineering | Pydantic | Python | RAG | Retrieval-Augmented Generation | Semantic Data Extraction | Semantic data | Terraform | Text Representation | “as-code”
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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