If you want to help us solve these problems, we want to hear from you.
Why this is an interesting machine learning problem
Data. Train on >50,000 hours of neural data from clinical trial participants
Nonstationarity. Tackle the tough open problem that neural activity drifts and we need to solve decoding while minimizing user recalibration
Co-adaptation. The brain adapts to your decoder while your decoder adapts to the brain
Strict constraints. The brain implant operates on a tight power and the participant experience requires optimizing every millisecond of latency
Your eval is a person. Success is a human being capable of doing something today that they couldn't do yesterday
What you'll work on
Train models on neural spike data across sessions and participants so a new user’s decode works out of the box, and stays working through weeks of drift without supervised recalibration
Design online adaptation that keeps the closed loop stable while both the model and the user are learning
Compress a full hand-and-arm decoder to run with a tight latency budget on the user’s device
Build the pre-training and post-training stack for voice synthesis: self-supervised representation learning on neural recordings, supervised fine-tuning on paired data, reinforcement learning with intelligibility and naturalness rewards, feeding a streaming vocoder that produces speech in real time
Define what evidence justifies shipping a model update to someone’s brain-computer interface, then build the eval and rollout infrastructure to meet that bar
Feed learnings back into the hardware platform. Our ASIC, thin-film arrays, and the rest of the brain implant are built in-house and follow your engineering gradient
You might be a good fit if you
Have designed, trained, and shipped real-time ML systems that people depend on
Have strong sequence modeling instincts (e.g., in speech, robotics, reinforcement learning, time-series, sensor fusion)
Prefer owning a problem end to end (data, model, deployment, eval) over one layer of a big stack
Are deeply curious to understand and expand human consciousness
Required: Bachelor’s degree (or higher) in Computer Science, a related field, or equivalent experience
Helpful (not required)
Familiarity with intracortical brain-computer interface decoding literature (e.g., handwriting and speech decoding, manifold alignment, unsupervised recalibration, cross-participant transfer)
Experience with model compression, quantization, or inference on constrained hardware
Experience in small-data or heavy-distribution-shift regimes
Note: No neuroscience background is required. We value simple solutions built from first principles, and some of our best decoding work has come from people who have zero experience with neuroscience.
Our tech stack
Machine Learning: PyTorch, JAX
Backend: Python, Rust, Swift, Bazel
Frontend: Typescript, SwiftUI
You may not be a fit if
You prefer remote work. This role is on-site five days a week. The lab, the robot, and your teammates are in the building. So is the job.
You’re looking for a 9-to-5 job. The pace is intense. People work hard here because a human being is waiting on the next release.
You prefer narrow, specific scope. We have small teams and high ownership.
Hiring process
Typically four weeks from start-to-finish.
Application: we ask for three concise examples of exceptional ability
Recruiter call: 30 minute video call with a member of our talent team
Hiring manager call: 45 minute technical video call with the hiring manager
Technical interview: 45 minute video call with an ML engineer about system design
On-site day: live presentation of a technical problem you’ve worked on plus a series of interviews with your future teammates
Founder interview: 15 minute interview with our Co-Founder, DJ Seo
Decision within 1 business day of your final interview.
Learn more
Expected Compensation
The anticipated base salary for this position is expected to be within the following range. Your actual base pay will be determined by your job-related skills, experience, and relevant education or training. We also believe in aligning our employees’ success with the company's long-term growth. As such, in addition to base salary, Neuralink offers equity compensation (in the form of Restricted Stock Units (RSU)) for all full-time employees.
Base Salary Range
$129,000—$331,000 USD
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