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.

Responsibilities

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.

Qualifications

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, TensorFlow, Hugging Face, LangChain, 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.

Nice to Have

Experience deploying AI systems in production.

Knowledge of multimodal (text, image, audio) model training.

Contributions to open-source AI projects or published research.

What We Offer

Competitive compensation

Flexible work environment.

Opportunity to work on frontier AI systems with real-world impact.

Full-time