Machine Learning Engineer Intern
NeuralinkRole Overview
Neuralink is hiring a Machine Learning Engineer Intern. This is a internship role in South San Francisco, California. Part of Neuralink's Data Science hiring, posted 2 weeks ago. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job description
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 to both technical and non-technical stakeholders
- Excellent communication and collaboration skills
- Strong coding skills, with a focus on clean, efficient, and scalable code development
Preferred Qualifications:
- Experience working with time series or unstructured data
Expected Compensation:
The anticipated hourly rate for this position is listed below.
What We Offer:
Full-time employees are eligible for the following benefits listed below.
- An opportunity to change the world and work with some of the smartest and most talented experts from different fields
- Growth potential; we rapidly advance team members who have an outsized impact
- Excellent medical, dental, and vision insurance through a PPO plan
- Paid holidays
- Commuter benefits
- Meals provided
- Equity (RSUs) *Temporary Employees & Interns excluded
- 401(k) plan *Interns initially excluded until they work 1,000 hours
- Parental leave *Temporary Employees & Interns excluded
- Flexible time off *Temporary Employees & Interns excluded
About Neuralink
Neuralink
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Frequently Asked Questions
How do I apply for the Machine Learning Engineer Intern position at Neuralink?
Use the Apply button above to submit your application directly to Neuralink. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Machine Learning Engineer Intern position at Neuralink located?
This position is based in South San Francisco, California. Neuralink has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Machine Learning Engineer Intern at Neuralink earn?
Neuralink has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Machine Learning Engineer Intern role at Neuralink posted?
This role was posted on June 22, 2026 (17 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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