Research Scientist (AI)

TL;DR

Research Scientist (AI): Leading research initiatives to train foundation models for a new enterprise agent, with an accent on developing novel architectures and training approaches for multi-modal vision-language models, reinforcement learning, and action models. Focus on designing and implementing supervised fine-tuning, preference learning, and reinforcement learning techniques, and advancing theoretical understanding of transformer architectures.

Location: Onsite in London, United Kingdom

Company

hirify.global acquired Convergence AI in June 2025 to establish its first engineering team in London, focusing on agent research and developing next-generation personal assistants for enterprise.

What you will do

• Lead research initiatives on training foundation models for a brand new enterprise agent.
• Design and implement novel supervised fine-tuning, preference learning, and reinforcement learning techniques.
• Develop innovative methods for data curation, including synthetic data generation pipelines.
• Conduct rigorous experimentation to optimize model performance.
• Advance the theoretical understanding of transformer architectures and their applications to multi-modal learning.
• Publish research findings in top-tier AI conferences and journals.

Requirements

• Deep knowledge of transformer architectures and vision-language models.
• Strong theoretical understanding of deep learning fundamentals.
• Expertise in training and fine-tuning open source models using techniques such as supervised fine-tuning or reinforcement learning.
• Proficiency in PyTorch and related frameworks.
• Experience with large-scale distributed training and inference using e.g., DeepSpeed, FSDP, Ray.

Nice to have

• PhD in Computer Science, Machine Learning, or related field.
• Strong publication record in top-tier ML conferences (NeurIPS, ICML, ICLR) or top journals.
• Research experience at leading academic or industrial research labs.
• Demonstrated expertise in reinforcement learning.
• Contributions to open-source ML frameworks.
• Experience developing novel datasets or data generation approaches.
• Background in causal reasoning or alignment research.

Culture & Benefits

• Work with a small team of hands-on researchers.
• Equipped with substantial GPU resources.