Machine Learning Engineer Intern
Neuralink - South San Francisco, California, United States
Posted May 30, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Deadline
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Where they hire
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About this role
Machine Learning Engineer Intern South San Francisco, California, United States About Neuralink: We are creating devices that enable a bi-directional interface with the brain. These devices allow us to restore movement to the paralyzed, restore sight to the blind, and revolutionize how humans interact with their digital world. Team Description: The Brain Computer Interface (BCI) Applications Team is responsible for delivering a product that gives people with paralysis the ability to control computers, phones, gaming consoles, and robotic arms with their minds at the same speed and functionality level as able-bodied people can. Furthermore, the team is focused on restoring speech for mute individuals and enabling direct, natural silent communication with AI agents. In this role, you'll work with neuroscientists, physicians, software engineers, and electrical engineers to develop the next-generation human-ready Brain-Computer Interface (BCI). Job Description and Responsibilities: We are hiring a Machine Learning Engineer Intern to develop novel neural decoders to increase control speed and accuracy, improve reliability, and expand functionality of BCIs. You will play a critical role in developing machine learning solutions and driving the successful execution of projects to achieve mission critical goals. You'll work with cross-functional teams to design new BCI functionalities and novel computer user interfaces. Required Qualifications: - Evidence in delivering high-impact projects either in academia or industry - Prior experience designing and building Machine Learning models - Deep understanding of machine learning concepts and fundamentals - Experience in analyzing complex datasets, driving insights, and communicating results in a simple and clear way
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