Principal AI/ML Engineer
Tasks
- Architect end-to-end AI/ML pipelines
- Build and operationalise production AI ML systems
- Communicate AI ML outcomes risks and behaviours
- Define responsible AI guardrails explainability and bias detection
- Develop deploy ML DL and LLM models
- Embed governance privacy security and compliance controls
- Establish model monitoring and observability
- Implement RAG pipelines and agentic AI architectures
- Integrate AI capabilities into enterprise platforms
- Manage drift bias fairness and performance
- Mentor engineers and set technical direction
- Translate AI research and strategy into production delivery
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agentic AI | Anthropic API | Azure | Bias detection | CI/CD | Crew AI | Data Drift | Data Drift Detection | Deep learning | Distributed Systems | Drift Detection | Explainable AI | Fault-tolerant | Fault-tolerant systems | LLM APIs | Langchain | Language Models | Large Language Models | Machine Learning | Milvus | Model Context Protocol | Model Evaluation | Monitoring | Observability | OpenAI API | Pinecone | Privacy | PyTorch | Python | RAG | Retrieval-Augmented Generation | SQL | Security Compliance | TensorFlow | Testing | TypeScript | Vector Databases | Weaviate
Education
Roles
AI/ML Engineer | Engineer | ML Engineer | Principal | Principal AI/ML Engineer
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