Materials Engineer
Neuralink · Fremont, CA · Brain Interfaces Hardware
About this role
Neuralink is hiring a mid-level Supply Chain Manager in the operations function based in Fremont, CA. The posting calls out experience with Python, Testing. Compensation is listed at $113,000–$209,000 per year.
- Role
- Supply Chain Manager
- Function
- operations
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Fremont, CA
- Department
- Brain Interfaces Hardware
More roles at Neuralink
Job description
from Neuralink careersAbout 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 Materials Engineering Team at Neuralink develops and qualifies high-performance, biocompatible materials for next-generation brain-computer interfaces. The team owns material characterization, hermetic packaging reliability, accelerated lifetime testing, and predictive simulation for implantable neural devices. We operate at the intersection of physical testing and computational modeling, closing the loop between experiment and simulation to drive design decisions.
Job Description and Responsibilities:
We are looking for a Mechanical Engineer who owns the full simulation-to-test loop for implant mechanical reliability. This person will build explicit dynamics FEA models, design and run physical tests, calibrate material models against experimental data, and validate predictions. You will work closely with materials engineers, microfabrication, and cross-functional reliability teams to ensure the implant meets impact, fatigue, and seal integrity requirements.
- Build, refine, and validate explicit dynamics Finite Element Analysis (FEA) models (LS-DYNA, Abaqus/Explicit) to predict mechanical response under high-strain-rate impact loading.
- Own the in-house mechanical testing pipeline end-to-end: design fixtures, prepare specimens, run tests (servo-hydraulic, drop tower, DIC), and correlate results to simulation using quantitative metrics (CORA, force-displacement overlay, DIC contour comparison).