GenAI/ML Engineers
Tasks
- Apply machine learning algorithms and deep learning models
- Automate AI pipeline using CI CD
- Build AI solutions on AWS
- Create prompt engineering and text embeddings pipelines
- Deploy machine learning models to production
- Design retrieval ranking and response synthesis
- Develop APIs for AI services
- Develop vector search with vector databases
- Generate embeddings and document chunking
- Implement RAG systems
- Implement secure authentication and authorization
- Perform data preprocessing and feature engineering
- Use Infrastructure as Code for cloud resources
- Validate AI outputs for responsible AI
Perks/Benefits
- N/A
Skills/Tech-stack
API Design | API Gateway | AWS | AWS CDK | AWS Lambda | Amazon API | Amazon API Gateway | Amazon Bedrock | Amazon S3 | Amazon SageMaker | CI/CD | CloudFormation | Csharp | Data Modeling | Data Privacy | Deep learning | Docker | Explainable AI | Faiss | FastAPI | Flask | IAM | Infrastructure as Code | Java | Langchain | Llamaindex | Machine Learning | Model Deployment | OAuth 2.0 | OpenSearch | Pinecone | Prompt engineering | Python | RAG | SQL | Secure API | Secure API Design | Terraform | Text Embeddings | Vector Databases | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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