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Data Scientist AWS Cloud

SelectMinds
Dallas, TX Full Time
POSTED ON 2/20/2025
AVAILABLE BEFORE 5/18/2025

Job Description

Job Description

Data Scientist (AWS Cloud)

Location : Dallas, TX (Hybrid – 3 days a week in the office)

Interview Process : Virtual Technical Screening followed by In-Person Interview

Are you an innovative Data Scientist with a passion for harnessing the power of AI / ML and cloud technologies?

Join our dynamic team, where you’ll solve real-world challenges using cutting-edge tools and AWS cloud services.

If you thrive on creating advanced AI / ML solutions and working in a collaborative, tech-forward environment, this opportunity is perfect for you!

Roles & Responsbilities :

  • Leverage 10 years of IT experience (including 5 years in Data Science ) to design and deploy AI / ML models in AWS cloud environments.
  • Build and optimize deep learning models using frameworks like TensorFlow and PyTorch on AWS infrastructure.
  • Apply advanced AI / ML techniques to large datasets, grounded in strong theoretical and practical expertise.
  • Implement cutting-edge methods, including :

Supervised and Unsupervised Learning

  • Deep Learning and Reinforcement Learning
  • Time Series Forecasting
  • Bayesian Statistics and Optimization
  • Develop and refine Large Language Models (LLMs) and Natural Language Processing (NLP) systems using open-source tools on AWS.
  • Independently design and build RAG (Retrieval-Augmented Generation) applications with AWS machine learning services and LLM models.
  • Work with AWS services like SageMaker , Lambda , EC2 , S3 , and Redshift to ensure scalable, high-performance AI / ML solutions.

    • Qualifications :

  • Expert-level Python programming skills focused on AI / ML research and deployment.
  • Proven experience with AWS machine learning services , including SageMaker , Lambda , and more.
  • Hands-on expertise with TensorFlow and PyTorch in AWS-based workflows.
  • The ability to independently design and deploy RAG applications using LLM models within AWS ecosystems.
  • Strong understanding of cloud-based AI / ML workflows and experience with high-performance computing in AWS environments.

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