Data Scientist with Generative AI

Job Role: Data Scientist with 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.