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Assistant Neurotechnology Jobs (NOW HIRING)

Subsense

Research Scientist in Neuroscience

Palo Alto, CA · On-site

$115K - $140K/yr

... in neurotechnology, we'd love to hear from you. Key Responsibilities * Design, build, and test ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Duke University

POSTDOCTORAL ASSOCIATE

Durham, NC · On-site

... assistants, and technicians. • Stay current with developments in cognitive neuroscience, neurotechnology, and wearable sensing, and integrate new techniques into ongoing research. Choose Duke. Min ...

Ampa, Inc.

Regulatory Affairs Specialist

Palo Alto, CA · On-site

$110K - $130K/yr

Ampa is a pioneering neurotechnology startup developing brain stimulation technology to help ... Corrections, Removals, and Recall Decisions: Assist with evaluation and documentation of potential ...

Duke University

POSTDOCTORAL ASSOCIATE

Durham, NC · On-site

Mentor and supervise graduate students, research assistants, and technicians. Stay current with developments in cognitive neuroscience, neurotechnology, and wearable sensing, and integrate new ...

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Assistant Neurotechnology information

What are the key skills and qualifications needed to thrive as an Assistant Neurotechnology, and why are they important?

To thrive as an Assistant Neurotechnology, you generally need a background in neuroscience, biomedical engineering, or a related field, often supported by a relevant degree or certification. Familiarity with neuroimaging tools, data analysis software like MATLAB or Python, and laboratory equipment is typically required. Strong attention to detail, teamwork, and effective communication are vital soft skills for collaborating with researchers and clinicians. These skills ensure accurate data collection, smooth research operations, and meaningful contributions to advancements in neurotechnology.

What are some common challenges faced by Assistant Neurotechnology professionals, and how can they be managed effectively?

Assistant Neurotechnology professionals often encounter challenges such as staying current with rapidly evolving technology, managing complex data from neuroimaging or electrophysiological studies, and ensuring accurate, ethical handling of sensitive patient information. To manage these, it's important to engage in continuous learning, maintain strong attention to detail, and collaborate closely with interdisciplinary teams including neurologists, engineers, and researchers. Effective communication and a willingness to seek guidance from senior team members also help in overcoming typical hurdles in this dynamic field.

What is the difference between Assistant Neurotechnology vs Assistant Biomedical Engineer?

AspectAssistant NeurotechnologyAssistant Biomedical Engineer
Required CredentialsTypically requires a bachelor's degree in neuroscience, biomedical engineering, or related fieldsRequires a bachelor's degree in biomedical engineering, bioengineering, or related disciplines
Work EnvironmentResearch labs, neurotechnology companies, healthcare institutionsHospitals, medical device companies, research facilities
Industry UsageFocused on developing and testing neurotech devices and systemsDesigning, testing, and maintaining medical devices and equipment
Common Search & ComparisonOften compared for roles supporting neurotech projects and researchCompared for roles in medical device development and biomedical research

Assistant Neurotechnology and Assistant Biomedical Engineer roles share similar educational backgrounds and work environments, often overlapping in healthcare and research settings. However, Assistant Neurotechnology specializes in neuro-specific devices and systems, while Assistant Biomedical Engineer has a broader focus on various medical devices and equipment.

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Assistant Neurotechnology jobs near you
Lead Embedded Firmware Engineer

Lead Embedded Firmware Engineer

OSI Engineering, Inc.

Palo Alto, CA

$300K - $400K/yr

Other

Posted 13 days ago

Job description

Lead Embedded Firmware Engineer

You will lead the firmware architecture and development for a breakthrough stealth-stage neurotechnology and brain-computer interface (BCI) startup building an AI-powered neural interface platform. This role owns the distributed-compute firmware ecosystem powering media and connectivity, biosignal acquisition, and always-on MCUs responsible for power management, privacy, and thermal control. The platform is redefining the future of human communication and human-computer interaction through tightly integrated wearable hardware, low-power embedded systems, and real-time intelligent processing.

  • Lead/Architect firmware across the distributed-compute platform: RTOS choice, task structure, inter-processor protocols, OTA, and time sync.
  • Own the runtime that hosts every subsystem, audio DSP, camera capture pipeline, biopotential acquisition, through specified interfaces with each subsystem lead.
  • Own the media and connectivity MCU pipeline, camera capture, audio runtime, wake-word, Wi-Fi streaming, and onboard logging, concurrently within strict CPU and memory budgets.
  • Drive low-power firmware on the always-on MCU: state machines for standby, assist, and continuous modes; hardware-enforced privacy; thermal throttling.
  • Build the multi-MCU time-sync layer that lets us correlate EEG, audio, and camera data downstream.
  • Establish the firmware engineering practices that scale: build and release pipelines, on-device telemetry, automated test, OTA with safe rollback, field debug tooling.
  • Partner with the EE lead on hardware bring-up and boot path; with the reliability lead on field telemetry, error handling, and diagnostic surfaces.
  • Bring up ASICs in collaboration with the EE and silicon teams
  • Ship the product by the end of year and build and lead the firmware team as we scale to production.


Responsibilities:

  • 10+ years of embedded firmware engineering, with at least one shipped consumer product where you owned firmware architecture end-to-end.
  • Deep expertise across embedded RTOSes and bare-metal ARM Cortex-M, with familiarity across at least two ecosystems (e.g., Zephyr, FreeRTOS, ESP-IDF, ThreadX, NuttX).
  • Hands-on experience hosting real-time DSP runtimes alongside wireless connectivity on resource-constrained MCUs — integrating algorithms owned by other teams.
  • Strong background in multi-radio coexistence (Wi-Fi + BLE), low-power state-machine design, and OTA with safe rollback.
  • Comfortable in the lab with JTAG/SWD, logic analyzers, and protocol sniffers — able to drive bring-up from first power-on through end-to-end functional demos.

Preferred Skills:

  • Deploying neural network inference to low-power MCUs or dedicated AI accelerators — model conversion, quantization, runtime integration.
  • Familiarity with on-device inference frameworks and edge AI runtimes.
  • Custom AI accelerator silicon, neuromorphic compute, or in-memory-compute platforms.
  • On-device wake-word or always-on voice activation engines.
  • Integrating biopotential acquisition over standard sensor buses.

Type: Fulltime

Location: Palo Alto, CA (Hybrid Schedule)

Salary Range: $300k - $400k/y (DOE)

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