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.The opportunityIn January 2024, a man paralyzed below the shoulders received a Neuralink implant. Within days he was playing chess and Civilization VI by imagining a cursor moving. That was our first product experience: computer control decoded from 1,024 electrodes in the brain’s motor cortex.Since then, 20+ people have been using the device, some for 17+ hours per day.We are now working on two problems nobody has solved.Decoding the full virtual arm. This requires deciphering 29 degrees of freedom against millisecond timescale neural spikes. The published state of the art is four degrees of individuated finger control (Willsey et al., Nature Medicine 2025). We aim to fully decipher human intent of controlling anything that a human hand is capable of doing, and build a product that our users rely on for their independence every day.Brain to voice.
The frontier of real-time voice synthesis from intracortical signals is intelligible roughly half the time and carries only coarse pitch control (Wairagkar et al., Nature, 2025). We are working towards prosodic speech, in users’ own voices, streaming fast enough to hold a natural conversation.If you want to help us solve these problems, we want to hear from you.Why this is an interesting machine learning problemData. Train on >50,000 hours of neural data from clinical trial participantsNonstationarity. Tackle the tough open problem that neural activity drifts and we need to solve decoding while minimizing user recalibrationCo-adaptation. The brain adapts to your decoder while your decoder adapts to the brainStrict constraints. The brain implant operates on a tight power and the participant experience requires optimizing every millisecond of latencyYour eval is a person. Success is a human being capable of doing something today that they couldn't do yesterdayWhat you'll work onTrain 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 recalibrationDesign online adaptation that keeps the closed loop stable while both the model and the user are learningCompress a full hand-and-arm decoder to run with a tight latency budget on the user’s deviceBuild 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 timeDefine what evidence justifies shipping a model update to someone’s brain-computer interface, then build the eval and rollout infrastructure to meet that barFeed 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 gradientRequired QualificationsHave designed, trained, and shipped real-time ML systems that people depend onHave 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 stackAre deeply curious to understand and expand human consciousnessBachelor’s degree in Computer Science, a related field, or equivalent experience Preferred QualificationsFamiliarity 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 hardwareExperience in small-data or heavy-distribution-shift regimesNote: 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 stackMachine Learning: PyTorch, JAXBackend: Python, Rust, Swift, BazelFrontend: Typescript, SwiftUIYou may not be a fit ifYou 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 processTypically four weeks from start-to-finish.Application: we ask for three concise examples of exceptional abilityRecruiter call: 30 minute video call with a member of our talent teamHiring manager call: 45 minute technical video call with the hiring managerTechnical interview: 45 minute video call with an ML engineer about system designOn-site day: live presentation of a technical problem you’ve worked on plus a series of interviews with your future teammatesFounder interview: 15 minute interview with our Co-Founder, DJ SeoDecision within 1 business day of your final interview.Learn moreExpected 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 USDWhat 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 fieldsGrowth potential; we rapidly advance team members who have an outsized impactExcellent medical, dental, and vision insurance through a PPO planPaid holidaysCommuter benefitsMeals providedEquity (RSUs) *Temporary Employees & Interns excluded401(k) plan *Interns initially excluded until they work 1,000 hoursParental leave *Temporary Employees & Interns excludedFlexible time off *Temporary Employees & Interns excluded
Machine Learning Engineer in austin at Unknown Company
This position is listed as full time and able to be worked remotely.