Lead AI Engineer
Tasks
- Automate AI/ML pipelines
- Build generative AI and agentic workflows
- Create RAG pipelines and embedding solutions
- Deploy models and manage feature stores
- Design data and AI architectures
- Design end to end AI and ML systems
- Embed safety evaluation and assurance
- Implement ethical explainable responsible AI
- Implement model monitoring and management
- Lead multi-disciplinary teams
- Orchestrate large language models
- Prepare data and build models
- Scale AI systems responsibly and reliably
Perks/Benefits
- Flexible working arrangements
- Hybrid working
- Mental health champions
- Mental health support apps
- Wellbeing programs
Skills/Tech-stack
A/B | A/B Testing | AWS | Agentic AI | Airflow | Amazon SageMaker | Anthropic | Azure | Azure AKS | Azure DevOps | Azure Machine Learning | B testing | CI/CD | Cloud Run | Databricks | Docker | Embeddings | Feature Stores | GCP | Generative AI | GitHub Actions | Google Cloud | Google Cloud Run | Hugging Face | Kubeflow | Kubernetes | LLM APIs | LLMOps | Lakehouse | MLflow | Machine Learning | Model Monitoring | NoSQL | OpenAI | Prompt evaluation | RAG | Relational databases | Vector Databases | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Lead | Lead AI Engineer | Learning Engineer | Machine Learning Engineer
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