Summary
Netholabs is building AI grounded in biological intelligence using neurobehavioural data and neural foundation models. The AI/ML Intern will support model training, data pipeline development, 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
- Work with biomechanical data, machine vision data, and robotics control problems
- 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 note 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
- Experience with machine vision or robotics problems
- 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
Qualifications
Must Haves
- Please note 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
Nice to Haves
- Experience with machine vision or robotics problems
- 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
- Internship duration of 6 months with a flexible start date
- Remote work, with on-site/hybrid possible
- Cross-training for the right person in neuroscience or robotics