Generative AI Data Scientist

Job Description About the Role

We’re looking for a Generative AI Data Scientist to design, train, and optimize AI models that power next-generation intelligent systems. You’ll work on projects involving large language models (LLMs), NLP, and multimodal data pipelines — helping turn research into production‑grade products.

• Develop and fine‑tune generative AI models (LLMs, diffusion, transformer‑based architectures).
• Build and manage data pipelines for model training, evaluation, and continuous learning.
• Design prompt engineering and retrieval‑augmented generation (RAG) frameworks.
• Collaborate with engineers and product teams to deploy scalable inference APIs.
• Evaluate model performance, bias, and data quality; implement monitoring systems.
• Contribute to model interpretability, safety, and responsible AI practices.

• MS or PhD in Computer Science, Machine Learning, Statistics, or related field.
• 3+ years of experience in ML/AI, with exposure to generative or transformer‑based models.
• Strong Python skills (PyTorch, Tensor Flow, Hugging Face, Lang Chain, etc.).
• Experience with vector databases, RAG, and fine‑tuning open‑weight models (e.g., Llama, Mistral).
• Familiarity with cloud ML environments (AWS Sagemaker, GCP Vertex, or Azure ML).
• Excellent problem‑solving and communication skills.

• Experience deploying AI systems in production.
• Knowledge of multimodal (text, image, audio) model training.
• Contributions to open‑source AI projects or published research.

• Competitive compensation
• Flexible work environment.
• Opportunity to work on frontier AI systems with real‑world impact.