Machine Learning Engineer Intern 100% Remote in London

We are at the forefront of integrating artificial intelligence with brain‑computer interface technologies. Projects leverage deep learning, generative models, and representation learning to decode and interpret brain activity. Our mission is to bridge the gap between AI and neuroimaging, driving innovation that is transparent and privacy‑focused.

We seek a motivated and skilled machine learning intern to join our Brain & AI team for 3 to 6 months. This role focuses on developing AI models that enhance our understanding of neural mechanisms, building encoding and decoding models, and applying this knowledge to real‑world brain‑computer interfaces.

Responsibilities

• Develop and evaluate scalable deep learning algorithms central to our brain decoding initiatives.
• Collaborate closely with data scientists to pioneer research in generative modeling and representation learning.
• Identify bottlenecks in data processing pipelines and devise effective solutions, improving performance and reliability.
• Maintain high standards of code quality, organization, and automation across all projects.
• Adapt machine learning and neural network algorithms to optimize performance in various computing environments, including distributed clusters and GPUs.
• Write and revise papers, communicate and disseminate results.

Qualifications

• Degree or currently involved in a PhD program in Computer Science, Statistics, Informatics, Physics, Math, Neuroscience, or another quantitative field.
• 1+ year of experience working in industry or research.
• Programming skills in Python, with experience developing machine learning algorithms or infrastructure using Python and PyTorch.
• Experience in deep learning techniques such as supervised, semi‑supervised, self‑supervised learning, and/or generative modeling.
• Scientific background and ability to formulate and test novel hypotheses with proper experiments, draw conclusions, and support claims.
• Experience managing unstructured datasets with strong analytical skills.
• Project management and organizational skills.
• Proven ability to support and collaborate with cross‑functional teams in a dynamic environment.

Preferred Qualifications

• Research experience in Computer Science, Statistics, Informatics, Physics, Math, Neuroscience, or another quantitative field.
• Scientific publications in AI and neuroscience conferences or peer‑reviewed journals.
• Familiarity with deep learning libraries such as PyTorch, Huggingface, Transformers, Accelerate, and Diffusers.
• Hands‑on experience in training and fine‑tuning generative models (diffusion models, large language models such as GPTs and LLAMAs).
• Experience with data and model visualization tools.
• Experience with non‑invasive neural data (fMRI, EEG, MEG) or invasive neural recordings (ECoG, MEA, etc.).