Principal AI/ML Engineer
Tasks
- Architect AI/ML systems
- Build agentic AI architectures
- Build end-to-end AI/ML pipelines
- Build retrieval-augmented generation pipelines
- Communicate AI system outcomes and risks
- Deploy evaluation frameworks
- Detect model drift bias and fairness issues
- Develop and deploy deep learning models
- Develop and deploy machine learning models
- Ensure explainability and security controls
- Establish responsible AI guardrails
- Implement monitoring and observability
- Integrate AI into enterprise platforms
- Mentor ML engineering teams
- Translate AI research into production solutions
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Anthropic API | Azure | Bias detection | CI/CD | Crew AI | Distributed Systems | Explainable AI | Fairness metrics | LLM | LLM-as-a-Judge | Langchain | Milvus | Model Context Protocol | Monitoring | Observability | OpenAI API | Pinecone | Privacy | PyTorch | Python | Retrieval-Augmented Generation | SQL | Security Compliance | TensorFlow | Testing | TypeScript | Vector Databases | Weaviate
Education
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