Tech Lead- AI & Gen AI

Key Responsibilities:

• Diffusion Model Optimization:
• Develop and optimize Diffusion models at scale for improved generative capabilities.
• Multi-modal Alignment:
• Work on aligning multi-modal data (e.g., text, image, and other forms) for seamless integration in generative tasks.
• Fine-tuning LLMs with RLHF:
• Apply Reinforcement Learning from Human Feedback (RLHF) to fine-tune Large Language Models (LLMs) for specific tasks or domains.
• Sparse Attention Mechanism Engineering:
• Design and implement Sparse Attention Mechanisms to improve the efficiency and scalability of generative models.
• Training Foundational Models:
• Lead efforts in training foundational models from scratch, focusing on enhancing the model's performance and capabilities.
• Latent Space Manipulation:
• Work on latent space manipulation and controllability in Generative Models, ensuring flexibility and control over model outputs.

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• 7-10 years of relevant work experience in software development with a strong focus on Generative AI applications.
• Proven expertise in Diffusion Models, LLM Fine-tuning, Sparse Attention Mechanisms, and Reinforcement Learning.
• Experience in training foundational models from scratch and handling latent space manipulation.
• Strong communication and collaboration skills to work effectively in cross-functional teams.

Preferred Skills:

• Experience with advanced AI/ML frameworks and tools.
• Expertise in scalable AI systems for large data sets.
• Ability to collaborate with research teams and stakeholders to drive innovation in Generative AI solutions.