Data Scientist; Generative AI

Job Summary
We are looking for a talented and innovative Data Scientist specializing in Generative AI to join our team. In this role, you will design, build, and deploy next-generation generative models across text, image, and video applications. Youll work at the forefront of AI, harnessing cutting-edge technologies like transformers, diffusion models, and GANs to develop impactful solutions. This is a hands-on, research-driven role where your contributions will directly influence product innovation and user experience.

Key Responsibilities

Design, train, and deploy generative models including GANs, VAEs, Diffusion Models, and Transformers.

Build scalable AI solutions for content generation across text, images, and video.

Optimize model performance, latency, and inference efficiency for production use.

Collaborate with engineering, product, and design teams to integrate AI capabilities into core products.

Conduct research on the latest Generative AI methodologies and apply findings to enhance model performance.

Ensure the responsible development and deployment of AI, incorporating ethical practices and bias mitigation.

Manage large-scale datasets: data acquisition, preprocessing, augmentation, and quality control.

Develop robust APIs and machine learning pipelines to operationalize AI models.

Present technical findings and strategic insights to internal stakeholders and leadership.

Required Qualifications

Bachelor's or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related discipline.

Proven experience with generative models such as GPT, Stable Diffusion, Style

GAN, or similar.

Proficient in Python and experienced with ML frameworks (PyTorch, Tensor Flow, or JAX).

Solid understanding of deep learning, NLP, computer vision, or multimodal AI systems.

Experience with cloud platforms (AWS, Azure, GCP) and MLOps best practices.

Hands-on experience with large-scale data processing tools (Spark, Dask, or similar).

Strong problem-solving ability and a research-oriented mindset.

Excellent collaboration and communication skills.

Preferred Qualifications

Experience fine-tuning LLMs and working with retrieval-augmented generation (RAG) architectures.

Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate).

Understanding of responsible AI principles and experience applying fairness or bias mitigation techniques.

Contributions to academic publications or open-source projects in the field of Generative AI.