Description

You will design and deploy cloud-based machine learning solutions and generative AI architectures on AWS.

This role is remote.

Responsibilities

• Manage end-to-end ML lifecycles including training jobs, inference, and processing in SageMaker.
• Build LLM applications using Langchain and fine-tuning techniques like Llama2.
• Design RAG architectures utilizing vector indexing with OpenSearch or Elasticsearch.
• Orchestrate NLP workflows using Airflow, StepFunctions, SageMaker Pipelines, or Kubeflow.
• Implement MLOps practices specifically for Generative AI models.

Required Skills

• 6+ years of experience in Machine Learning.
• Proficiency with AWS SageMaker for training and inference.
• Hands-on experience with LLMs and fine-tuning (Llama2).
• Experience with Langchain and GenAI frameworks including vertexAI, OpenAI, and AWS Bedrock.
• Deep learning expertise in Transformers, BERT, and Attention models.
• Knowledge of RAG architecture and vector databases (OpenSearch, Elasticsearch).
• Experience with NLP workflow orchestration (Airflow, StepFunctions, SageMaker Pipelines, or Kubeflow).
• Practical application of clustering and neural networks.

Preferred Skills

• Experience working on Edtech use cases.
• General software development experience.

Key Skills

Education

Any graduate