Machine Learning Engineer Intern

WHO WE ARE

At Hiverge, we're transforming the algorithms the world runs on. We're building a platform that orchestrates thousands of AI research agents to discover new algorithms to solve some of the world's most challenging optimisation problems. Our founding team is composed of world-class researchers from Google DeepMind and the University of Cambridge, having co-developed AlphaTensor, FunSearch, AlphaEvolve, and Nobel Prize-winning AlphaFold. At Hiverge, you will be working with the brightest minds in AI, algorithms, and mathematics. If you're passionate about AI and eager to shape transformative technologies, we'd love to hear from you.

ABOUT THIS ROLE

We are seeking a Machine Learning Engineer Intern to work at the intersection of AI research, software engineering, and optimisation. You will help develop and evaluate our AI discovery engine, experiment with agentic systems, and contribute to solving challenging problems. You will:

• Help research and implement techniques to improve the reasoning, planning, and problem-solving capabilities of AI agents, including post-training approaches.
• Develop and experiment with agentic systems that collaborate to solve complex optimisation problems.
• Build evaluation frameworks and run experiments to measure and improve system performance.
• Develop tools and infrastructure to support efficient, reproducible experimentation.
• Collaborate closely with researchers and engineers to turn new ideas into working systems.

QUALIFICATIONS

• Strong programming skills in Python and a solid foundation in algorithms and software engineering.
• Familiarity with machine learning concepts and an interest in language models and AI.
• Strong analytical and problem-solving skills, demonstrated through academic work, personal projects, open-source contributions, or internships.
• Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Mathematics, Engineering, or a related field, or equivalent practical experience.

WHAT SETS YOU APART

• Experience with LLM post-training, reinforcement learning, or fine-tuning.
• Experience with agentic systems, planning, or reasoning frameworks.
• Familiarity with algorithms, mathematical optimisation, or evolutionary methods.
• Experience with PyTorch, JAX, or modern LLM tooling.
• Experience building evaluation frameworks or experimentation infrastructure.
• Contributions to open-source projects or academic research.

We offer competitive compensation and a stimulating work environment, with the opportunity to contribute to the future of AI. Outstanding interns may be considered for a full-time Machine Learning Engineer position upon completion of the internship.