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Senior Data Scientist

Role Overview
We are seeking a highly skilled and experienced Senior Data Scientist with a strong background in Python programming, NLP, and AI/ML technologies, including advanced concepts and practical experience with FastAPI/Flask, Transformers, and Generative AI (GenAI). The ideal candidate should have a minimum of 5 years of experience in Data Science and Machine Learning, with a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in cloud services such as AWS and Azure, as well as MLOps practices, will be critical in this role.

Responsibilities

Your technical responsibilities include but are not limited to: Design and implement AI/ML solutions using NLP and Transformer models, and leverage GenAI capabilities to enhance application intelligence. Manage AWS cloud infrastructure and services including S3, EC2, Lambda, RDS, Glue, Sagemaker, EMR, and Step Functions to build and deploy scalable machine learning models. Utilize AWS Batch for efficient batch computing and maintain code repositories with GIT for version control and collaboration. Apply MLOps and LLMOps methodologies to automate the machine learning lifecycle, ensuring models are scalable, maintainable, and reliable. Develop and maintain APIs using FastAPI for seamless integration of AI/ML models into applications. Work with Bedrock and EKS to orchestrate containerized applications, ensuring high availability and scalability of AI services.

 

Requirements

Proven track record with at least 5 years of experience in a technical role focused on AI/ML. Expertise in AI/ML frameworks, NLP, and Transformer technologies. Strong experience with AWS cloud services, particularly for data processing and machine learning. Proficiency in MLOps practices and familiarity with LLMOps. Experience with FastAPI or similar frameworks for API development. Knowledge of container orchestration with AWS EKS and Bedrock.

Good to Have Skills

Team handling experience and architecture design experience. Proficiency in creating and delivering Powerpoint presentations. Knowledge of Responsible AI practices and Nvidia MLOps platform. Experience with fine-tuning open-source AI/ML models. Familiarity with DevOps practices, including continuous integration, deployment, and monitoring of AI models.

 

 

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