Job Description
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.