Architect - Machine Learning - GenAI

The Architect - Machine Learning - GenAI will be responsible for designing end-to-end solution architectures for model training, deployment, and retraining using native AWS services. This role focuses on implementing advanced machine learning and generative AI solutions to solve complex business problems.

Responsibilities

• Design and implement cloud ML solutions on AWS, leveraging services like Sagemaker, Lambda, and others.
• Develop applications using LLMs, Langchain, and GenAI frameworks such as AWS Bedrock and OpenAI.
• Fine-tune large language models (LLMs) and Generative AI models, specifically LLama2.
• Architect and implement Retrieval Augmented Generation (RAG) systems using vector indexing tools like Opensearch and Elasticsearch.
• Perform prompt engineering and optimize few-shot techniques to enhance model performance.
• Conduct model evaluation, hyperparameter tuning, and ensure task generalization and interpretability.
• Collaborate with ML and integration engineers to deliver contextually appropriate responses in web applications.
• Design software architecture and utilize workflow orchestration tools like Airflow, StepFunctions, or Kubeflow.
• Work with cross-functional teams including Developers, QA, and Project Managers.

Requirements

• 12+ years of relevant hands-on technical experience in implementing and developing cloud ML solutions on AWS.
• Strong familiarity with LLM trends, open-source platforms, and deep learning concepts (Transformers, BERT, Attention models).
• Thorough understanding of NLP techniques for text representation and modeling.
• Proficiency in various machine learning techniques (supervised/unsupervised, clustering, decision trees, neural networks).
• Ability to design end-to-end architectures for model lifecycle management.

Preferred Qualifications

• Experience working with customers or workloads in the Edtech domain.
• Additional experience with software development.