AI/ML Engineer
Tasks
- Apply retrieval augmented generation to improve retrieval
- Architect agentic framework for financial advisors
- Architect data models for AI ML initiatives
- Build data pipelines
- Collaborate with DevOps to monitor production AI ML
- Deploy and optimize AI models in cloud
- Design, develop, and deploy AI/ML solutions
- Develop scalable machine learning pipelines
- Implement MLOps best practices
- Implement OCR capabilities and integrate with vector databases
- Implement generative AI agent based systems and machine learning models
- Maintain AI model performance and scalability
- Provide technical guidance and mentorship
- Share knowledge with teams
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agentic Systems | Amazon Bedrock | Amazon SageMaker | CI/CD | Data Pipelines | DevOps | Docker | Generative AI | Kubernetes | MLOps | Machine Learning | OCR | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Scikit-learn | TensorFlow | Vector Databases
Education
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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