Research Scientist (AI)

TL;DR

Research Scientist (AI): Conduct advanced research and development on Gemini Diffusion, a state-of-the-art text diffusion model, to accelerate generative AI capabilities with an accent on paradigm-shifting innovations and large-scale experimental validation. Focus on designing, prototyping, and advancing large-scale diffusion models and collaborating closely with AI teams to integrate breakthroughs into production.

Location: London, UK (onsite)

Company

hirify.global is a leading AI research company focused on advancing artificial intelligence for public benefit and scientific discovery with a strong emphasis on safety and ethics.

What you will do

• Brainstorm and develop disruptive ideas in text diffusion and generative AI.
• Prototype and contribute directly to Gemini Diffusion research projects.
• Design and execute experimental research to solve key challenges in diffusion models.
• Validate theoretical and practical impacts of research at large scale.
• Collaborate with other AI teams to transition research into production systems.
• Advance architecture, algorithms, and capabilities of large-scale diffusion models.

Requirements

• Location: Must be based in London, UK for onsite work.
• Advanced degree or equivalent experience in computer science, engineering, science, or mathematics.
• Academic or research experience in machine learning, including publications.
• Experience with LLMs, Transformers, Diffusion models, and large-scale distributed training.
• Proficiency in Python and scientific libraries such as Numpy, Scipy, JAX, PyTorch, or TensorFlow.
• Strong communication skills and deep understanding of relevant mathematics and statistics.

Nice to have

• Experience building software in open source or product environments.
• Knowledge of large-scale system design and distributed systems.
• Experience with distributed computation for ML accelerators.
• Programming skills in C++.
• Data engineering and visualization expertise.

Culture & Benefits

• Commitment to diversity, equal opportunity, and inclusive work environment.
• Focus on fundamental research and technical innovation.
• Collaborative, multi-disciplinary team environment.
• Investment in training and continual learning.