Machine Learning Engineer

Netholabs is building a foundation model of the brain and behavior across species using large-scale multimodal neural and behavioral data. The Senior Machine Learning Engineer will design and train core generative models, develop representations across neural signals and behavior, lead scalable training and evaluation, and contribute to research and production-quality modeling systems.

Responsibilities:

• Design, train, and iterate on large generative (recurrent or transformer-based) models over multimodal neural and behavioral data
• Own training at scale: data loading, distributed training, hyperparameter optimization, and evaluation
• Develop representations that capture structure across species and modalities
• Train models on animal and human behavioral data as well as direct neural data
• Define and run experiments to test modeling choices, and build the evaluation that tells us whether the model is learning what we need
• Draw on the neuroscience and sequence-modeling literature to inform architecture and training
• Turn research findings into reproducible, production-quality model code
• Partner with the data engineering team on data readiness and with the research team on what the model needs to capture
• Contribute to the shared modeling roadmap alongside our existing ML engineer