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Sr. Data Scientist Generative AI

Virtual NetworxAtlanta, GA🇺🇸United StatesPosted 2 Sept 2026

Why This Role Stands Out

This hybrid role offers an exciting opportunity to drive innovation in Generative AI, developing cutting-edge models and mentoring emerging talent. You'll thrive here if you have a strong background in machine learning and a passion for staying ahead of the curve in AI advancements. Apply now to join a forward-thinking team and shape the future of technology.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Atlanta, GA, United States
Posted
23 hours ago
DockerFastAPIAWSMachine LearningScikit-learnAzureDeep LearningGenerative AIGitGoogle CloudJenkinsKerasKubernetesPyTorchPythonTensorFlow

Job Description

Job Role:Sr. Data Scientist Generative AI

Location: Atlanta, GA | US

Duration: Long Term

JOB DUTIES & RESPONSIBILITIES:

  • Design, develop, and deploy generative AI models for various applications with a focus on text generation and sematic entity extraction.
  • Collaborate with stakeholders to identify business needs, define project scopes, and establish data-driven solutions.
  • Mentor junior data scientists/interns, providing guidance on best practices and industry standards.
  • Stay up to date with the latest research and advancements in Generative AI and related fields.
  • Collaborate with other teams, such as engineering and product management, to integrate models into production environments.
  • Establish and maintain documentation for models, algorithms, and processes.
  • Ensure all projects meet quality, performance, and security standards.
  • Communicate complex concepts and findings effectively to both technical and non-technical audiences.

WORK EXPERIENCE

  • Proven experience (3-5 years) as a Data Scientist or Machine Learning Engineer, with experience in deploying Generative AI based solutions in production.
  • Experience working on cutting-edge technologies to solve problems using Retrieval Augmented Generation (RAG), Fine tuning LLMs, Prompt tuning, Graph RAGs, Knowledge graphs, etc.
  • Strong background in machine learning, deep learning, and probabilistic modeling.
  • Proficiency in modern data science tools and frameworks, such as PyTorch, Tensorflow, JAX, Scikit-learn, and Keras.
  • Experience designing and implementing large-scale data pipelines and processing systems.
  • Experience working with server-side frameworks like FastAPI as well as API development, documentation, and versioning.
  • Familiarity with cloud platforms (AWS, Google Cloud Platform, or Azure), CI/CD tools (Jenkins) and containerization technologies (Docker, Kubernetes).
  • Strong programming skills in Python and experience working with version control systems (Git).
  • Experience mentoring junior colleagues and interns.

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