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# Machine Learning Engineer

- **Company:** Neuralink Corp.
- **Location:** South San Francisco, CA, United States (Remote available)
- **Salary:** $129,000.0 - $331,000.0
- **Contract:** Temporary contract
- **Skills:** Clinical Data Repository, Hardware Platform Interface, Machine Learning, Model Compression, Sensor Fusion, TypeScript, Reinforcement Learning, Application Specific Integrated Circuits, Pytorch, Swiftui, Discretization, Information Technology, Machine Learning Operations, Front End Software Development, Feature Extraction, Decoding
- **Published:** November 4, 2026
- **Apply:** https://www.careerbuilder.com/job-details/machine-learning-engineer-south-san-francisco-ca--dec98374-0313-4681-a9b2-d4af26a65636

## About the Role

Machine Learning, Medicine, Product Development, Problem Solving Skills, Clinical Trial, Clinical Data, Implants, Budgeting, Reinforcement Learning, Thin Film, * 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.

## Description

* 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, * 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.