DE&A - AIML - Data Science - Machine Learning
Tasks
- Build AI agents and autonomous workflows
- Build reusable AI frameworks and best practices
- Collaborate with stakeholders to identify AI use cases
- Deploy and monitor AI solutions in production
- Design AI/ML solutions
- Develop and deploy generative AI applications
- Evaluate model performance and reliability
- Fine tune and monitor ML and generative AI models
- Implement RAG architectures
- Integrate AI solutions with REST APIs and microservices
Perks/Benefits
- N/A
Skills/Tech-stack
AI Agents | AWS | Azure | CI/CD | Cloud Computing | Cloud platform | Deep learning | Docker | Embeddings | Generative AI | Google Cloud | Google Cloud Platform | Kubernetes | Language Models | Large Language Models | Machine Learning | Microservices | Prompt engineering | PyTorch | Python | RAG | REST APIs | Retrieval-Augmented Generation | Semantic Search | TensorFlow | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Engineer
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