Description

You will own the development and deployment of generative AI systems across multiple modalities.

This role is hybrid.

Responsibilities

• Run end-to-end experiments on transformer-based architectures including LLMs, diffusion, and multimodal models.
• Prototype, benchmark, and optimize generative AI techniques for text, audio, and video applications.
• Build automated evaluation pipelines to score audio, video, and image quality outputs.
• Experiment with cross-modality integration, such as audio–video synchronization.
• Take complete ownership of projects from initial concept through to production deployment.

Required Skills

• 4–10 years of experience in applied ML/Data Science with significant generative AI exposure.
• Deep understanding of transformer architectures, training dynamics, and model optimization.
• Expertise in core ML frameworks such as PyTorch and TensorFlow.
• Strong coding proficiency in Python.
• Experience working with LLMs and multimodal architectures.
• Familiarity with deployment frameworks like FastAPI or model servers.
• Ability to design and implement automated evaluation systems for generative outputs.
• Experience with fine-tuning and scaling strategies for production systems.

Key Skills

Education

Any Graduate