AI/ML Research Engineer

Responsibilities

• Develop and shape foundational AI/ML systems that power next-generation brain-computer interfaces
• Own core modeling work end-to-end, from dataset curation to designing and running training experiments
• Establish reproducible training pipelines for large-scale neural modeling and experimentation
• Write and review model and pipeline code, launch training runs, and debug issues at scale
• Collaborate with neuroscience and data teams to ground modeling choices in neural signal characteristics
• Deliver scaling, pretraining, and ablation experiments to guide future modeling decisions

Requirements

• 5+ years of hands-on experience building and training deep learning models, or a PhD in a related field with applied industry experience
• Proficiency in Python and strong experience with PyTorch or similar modern ML frameworks
• Solid software engineering practices, including version control, testing, and code review
• Experience with experimental design, rigorous analysis, and making data-driven decisions
• Ability to work in ambiguous, research-oriented environments with heterogeneous datasets

Preferred Qualifications

• Experience with neural signal processing, electrophysiology, or other biosignal domains
• Background in self-supervised learning, representation learning, or transfer learning
• Experience training models at scale using distributed systems or multi-GPU environments
• Knowledge of model efficiency techniques such as distillation, quantization, or pruning
• Experience in regulated or safety-critical environments like medical devices or healthcare AI

About the Company

Blackrock Neurotech builds the next generation of human capability through brain-computer interfaces designed to be safe, scalable, and trusted. We work to restore independence, identity, and agency to people with neurological conditions by creating seamless interfaces between human intent and technology.