Location : Remote
Mandatory Skills : AWS Sagemaker, AWS BedRock, Generative AI
Job Overview :
AWS Experience - AWS Sagemaker is required, AWS BedRock would be a nice to have.
Model Building, Accuracy Metrics, Finetuning - standard Data Science skillset.
Proven expertise in model finetuning for LLMs - PEFT, LORA techniques would be a big plus.
Able to understand what technique to use for data type.
RAG Experience would be great to have - similar to AI Engineer.
Machine Learning Engineering :
- Develop, train, and deploy ML models, ensuring they are optimized for production environments.
- Create and maintain automated feedback loops to enhance model accuracy and performance.
- Implement ML pipelines for continuous evaluation and refinement of models in production.
AI Orchestration & Integration :
Integrate Large Language Models (LLMs) into business applications.Build AI orchestration systems to manage the end-to-end lifecycle of AI models, including deployment and scaling.Work with Vector Databases (VectorDB) to store and query high-dimensional data for AI applications.Set up evaluation metrics and processes to assess model performance over time.Create feedback loops using real-world data to improve model reliability and accuracy.Text-to-SQL & Generative AI-driven Solutions :
Develop GenAI-driven Text-to-SQL solutions to automate database queries based on natural language input.Optimize GenAI workflows for database interactions and information retrieval.Embedding / Chunking & Prompt Engineering :
Design and implement embedding and chunking strategies for scalable data processing.Utilize prompt engineering techniques to fine-tune the performance of AI models in production environments.Required Qualifications :
Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field.Proven experience in building, deploying, and maintaining ML models in production environments.Proficiency in programming languages like Python, and frameworks such as TensorFlow, PyTorch, or similar.Familiarity with LLMs, VectorDB, embedding / chunking strategies, and AI orchestration tools.Strong understanding of model evaluation techniques and feedback loop systems.Hands-on experience with Text-to-SQL and prompt engineering methodologies.Knowledge of cloud platforms (AWS) and containerization tools (Docker, Kubernetes).J-18808-Ljbffr
