Machine Learning Engineer

Requirements

Experience writing production-level C/C++/Rust and Python

Proven track record of designing, building, and shipping real-time ML products

Strong foundation in signal processing, algorithms, and software engineering principles

Bachelor’s degree in relevant field or equivalent experience

What the job involves

The BCI team develops the software and systems that communicate with the brain. These systems decode raw neural signals into useful actions, such as moving a cursor, typing, or actuating a robotic arm

Additionally, real-world data, such as video feeds, can be encoded into neural data to project images into the visual cortex. We also work closely with users to gather feedback, make improvements, and fundamentally reshape the user experience and interface of the BCI

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain

You will have access to the most cutting-edge neural interface hardware and develop state-of-the-art neural encoders and decoders. No prior knowledge of neuroscience is required; we value simple solutions grounded in first principles

Neuralink designs all hardware in-house, from custom ASICs to thin-film arrays. There is no part of the technical design that cannot change. Learnings from your work will directly influence next-generation device architecture

Telepathy Product: Develop and refine models that decode neural data, enabling individuals with paralysis to reliably type at 35 words per minute or control robotics arms for activities of daily living

Blindsight Product: Formulate research questions to guide the development of neural networks and signal processing algorithms that will restore vision to those affected by blindness

Utilize your fundamental understanding of neural networks and data science to develop models that serve as the foundation for machine learning applications for BCI

Lead the team by performing at a high standard, setting the bar for how we build and operate our systems

Inform our hardware roadmap by understanding users and identifying the product features that would have the greatest impact on their quality of life

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