[Remote] AI/ML Internship

Note: The job is a remote job and is open to candidates in USA. Netholabs is building AI grounded in biological intelligence using neurobehavioural data and neural foundation models. The AI/ML Intern will support model training, data pipelines, experimentation, and applied machine learning projects involving robotics and embodied AI.

Responsibilities

• Support training, fine-tuning, and evaluation of neural foundation models
• Run experiments, track results, and help iterate on model architectures
• Help benchmark model performance and write up findings
• Build and maintain data pipelines for petascale neurobehavioural datasets
• Clean, preprocess, and structure multi-modal data (video, sensor, physiological) for training
• Help keep experiment tracking, datasets, and compute usage organized
• Support applications of trained models to robotics and embodied-agent tasks
• Prototype small tools, scripts, and demos to test model capabilities
• Contribute to internal documentation as work progresses

Skills

• Please not the successful candidate must be eligible to work in the US, we are not able to sponsor visas at this time
• Strong Python skills and comfort working in a Linux/command-line environment
• Solid foundation in ML fundamentals (e.g., through coursework, projects, or research)
• Experience with at least one deep learning framework (PyTorch preferred)
• Experience training ML models on time-series datasets
• Curious, self-directed, and comfortable working with ambiguity in a fast-moving research environment
• Good communication; able to document work clearly as you go
• No prior neuroscience or robotics experience required; we will cross-train the right person
• Exposure to large-scale model training or distributed compute
• Experience with data pipelines, structured storage, or large dataset handling
• Familiarity with robotics, sensorimotor learning, or embodied AI
• Background in neuroscience, behavioural science, or related fields

Benefits

• Remote work; on-site/hybrid possible
• Hands-on exposure to how a neural foundation model is built
• We will cross-train the right person

Company Overview