# Machine Learning Engineer at Neuralink Machine Learning Engineer at Neuralink in Austin, Texas, United States; South San Francisco, California, United States. Remote, full-time. Posted June 29, 2023. - Company: Neuralink - Location: Austin, Texas, United States; South San Francisco, California, United States - Workplace: Remote - Job type: Full-time - Posted: 2023-06-29 - Apply: https://boards.greenhouse.io/neuralink/jobs/5663271003?gh_jid=5663271003 - Source: https://jobmagic.ai/jobs/machine-learning-engineer-neuralink-9kxpay ## 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. ### **The opportunity** In 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 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*