Required Skill and Experience
Experience in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Experience in Design, develop, and fine-tune machine learning models, particularly those involving LLMs and generative AI.
Experience with AWS services, especially Bedrock, S3, EC2, and Lambda Familiarity with ML Ops practices and tools for model deployment and monitoring.
Experience with AWS SageMaker for model development and model deployment.
Experience with developing and deploying AI Agents for business problems.
Experience in optimizing and adapt prompt engineering strategies to improve model performance and relevance.
Experience with LLMs (e.g., OpenAI, Anthropic, Cohere) and prompt engineering.
Experience in understanding quantitative/
statistical/ML/AI modeling methodologies.
Experience in ML engineering, including hands-on experience with Generative AI/LLMs.
Preferred Skill and Experience
Experience in building and maintaining scalable data pipelines and APIs to support ML workflows.
Knowledge of data privacy and security best practices in cloud environments.
Familiarity with containerization (Docker) and container orchestration is a plus.
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