Senior Data Scientist Generative AI

Position: Sr. Data Scientist Generative AI

Location: Atlanta, GA (Hybrid - 3 days Onsite - 2 days Remote)

Visa: H1, USC

Rate: depends on experience

Job description:

Summary:

We are seeking a talented Senior Data Scientist with expertise in Generative AI to join our team. This role will report to the Director of Artificial Intelligence and will be based out of the Atlanta office. The Senior Data Scientist will design , develop, and implement cutting-edge generative models , driving innovation while providing technical leadership to a team of data scientists . You will work closely with engineers, product managers, and researchers to identify opportunities, design solutions, and deliver high-impact projects that leverage Generative AI technologies.

Job Duties & Responsibilities:

1. Design, develop, and deploy generative AI models for various applications with a focus on text generation and semantic entity extraction.
2. Collaborate with stakeholders to identify business needs, define project scopes, and develop data-driven solutions.
3. Mentor junior data scientists and interns, providing guidance on best practices and industry standards.
4. Stay updated with the latest research and advancements in Generative AI and related fields.
5. Collaborate with engineering and product management teams to integrate models into production environments.
6. Establish and maintain documentation for models, algorithms, and processes.
7. Ensure that all projects meet quality, performance, and security standards.
8. Effectively communicate complex concepts and findings to both technical and non-technical audiences.

Work Experience & Education Requirements:

1. Master's degree in Computer Science, Statistics, Mathematics, or a related field (required).
2. Ph.D. in a related field (preferred).
3. Proven experience (3-5 years) as a Data Scientist or Machine Learning Engineer with a focus on deploying Generative AI-based solutions in production environments.
4. Experience working with cutting-edge technologies to solve problems using Retrieval Augmented Generation (RAG), fine-tuning LLMs, prompt tuning, Graph RAGs, and knowledge graphs.
5. Strong background in machine learning, deep learning, and probabilistic modeling.
6. Proficiency with modern data science tools and frameworks such as PyTorch, TensorFlow, JAX, Scikit-learn, and Keras.
7. Experience designing and implementing large-scale data pipelines and processing systems.
8. Hands-on experience with server-side frameworks like FastAPI, API development, documentation, and versioning.
9. Familiarity with cloud platforms (AWS, Google Cloud Platform, or Azure), CI/CD tools (e.g., Jenkins), and containerization technologies (Docker, Kubernetes).
10. Strong programming skills in Python and experience working with version control systems like Git.
11. Excellent communication and teamwork skills.
12. Experience mentoring junior colleagues and interns.