AI Engineer - Sydney
AUD 100K-130K (estimate) Mid-level Full Time
Tasks
- Apply prompt engineering and function calling
- Build LLM-powered applications
- Build MLOps and LLMOps pipelines
- Collaborate with stakeholders to deliver AI products
- Create scalable data pipelines
- Design deploy enterprise AI solutions
- Design retrieval architectures with vector databases
- Develop RAG architectures
- Develop multi-agent systems
- Embed Responsible AI and governance controls
- Identify and mitigate model risks
- Implement CI/CD pipelines
- Implement agentic workflows
- Integrate structured and unstructured data
- Manage container orchestration deployments
- Monitor models and applications
- Perform model evaluation and tuning
- Run experimentation and benchmarking
- Support compliance privacy and security requirements
- Translate business needs into technical architectures
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS | Automated testing | CI/CD | Cloud platform | CrewAI | Docker | ELT | ETL | Experiment tracking | Fine Tuning | Function Calling | Generative AI | Google Cloud | Google Cloud Platform | Infrastructure as Code | Kubernetes | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | MLOps | Machine Learning | Microservices | Microsoft Azure | Model Evaluation | Model Monitoring | Prompt engineering | RAG | Retrieval-Augmented Generation | Vector Databases | “as-code”
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
Cities
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