Description

Design & Implementation
Develop and implement scalable Al agent architectures aligned with business requirements, leveraging foundational models.
Bedrock Model Expertise
Fine-tune and deploy Amazon Bedrock models (e.g., Large Language Models and multimodal models) for specific use cases.
Implement solutions involving vector-based retrieval and Retrieval-Augmented Generation (RAG).
Optimization
Improve model performance while ensuring optimal balance between computational efficiency and cost.
System Reliability
Ensure deployed Al systems are robust, accurate, scalable, and maintainable over time.
Innovation
Stay current with advancements in AI/ML technologies and continuously enhance existing solutions. Collaboration
Work closely with data scientists, software engineers, product managers, and stakeholders to translate Al research into production-ready systems.
Data & Infrastructure
Manage large datasets and model lifecycle tools (e.g., MLflow).
Implement containerization solutions (e.g., Docker) to ensure reproducibility and scalability.
Technical Skills
Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
Hands-on experience with MLOps tools (e.g., MLflow, BentoML, Kubeflow).
Solid understanding of LLMs, LangChain, and vector databases.
Experience working with AWS Bedrock services and APIs.
Familiarity with Docker, CI/CD pipelines, and cloud infrastructure

Key Skills

Education

Any Gradute