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Neural Interface Research Jobs in California (NOW HIRING)

Hark

On-Device Research Engineer

San Jose, CA · On-site

$120K - $300K/yr

We're pairing that intelligence with next-generation hardware to create a universal interface ... Familiarity with neural architecture search and hardware-aware NAS * Background shipping voice ...

Hark

On-Device Research Engineer

San Jose, CA · On-site

$120K - $300K/yr

We're pairing that intelligence with next-generation hardware to create a universal interface ... Familiarity with neural architecture search and hardware-aware NAS * Background shipping voice ...

subsense

Experimental Research Engineer

Mountain View, CA · On-site

$120 - $140/hr

... interface powered by plasmonic and magnetoelectric nanoparticles. Our mission is to unlock direct ... Support biological experiments involving cell cultures, neural systems, and related laboratory ...

Epia Neuro

Staff Robotics Hardware Engineer

Alameda, CA · On-site

$150 - $210/hr

Its platform integrates implantable neural interfaces, adaptive algorithms, and assistive devices ... Experience transitioning systems from research prototypes toward scalable or production-ready ...

SupportFinity™

Staff Neuroscientist

Santa Clara, CA · On-site

$140 - $230/hr

Extensive Neuro‑engineering Experience: 2+ years of post‑PhD experience in a research or industrial setting, specifically focused on the interface between neural tissue and engineered systems.

New

Alljoined

Software Engineer

San Francisco, CA · On-site

... neural decoding technology while working alongside world-class researchers pushing the boundaries of what's possible in brain-computer interfaces Qualifications : Required : • 5+ years of ...

Neuralink

Neuroengineer, Next Gen

Fremont, CA · On-site

$122K - $226K/yr

Neuroengineer, Next Gen We are creating devices that enable a bi-directional interface with the ... Run and support research sessions in coordination with software engineers, field engineers, and ...

Neuralink

Neuroengineer, Next Gen

South San Francisco, CA · On-site

$122K - $226K/yr

We are creating devices that enable a bi-directional interface with the brain. These devices allow ... Run and support research sessions in coordination with software engineers, field engineers, and ...

Neuralink

Neuroengineer, Next Gen

South San Francisco, CA · On-site

$122K - $226K/yr

We are creating devices that enable a bi-directional interface with the brain. These devices allow ... Run and support research sessions in coordination with software engineers, field engineers, and ...

Astera

Experimental Neuroscientist

Emeryville, CA · On-site

$120K - $220K/yr

... and interface hardware to software and computational methods, and to use them to study neural ... All animal research is conducted under IACUC-approved protocols with a deep commitment to animal ...

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Neural Interface Research information

What is neural interface research?

Neural interface research is the scientific study and development of technologies that connect the nervous system, particularly the brain, with external devices or computers. These interfaces, often called brain-computer interfaces (BCIs) or neural prosthetics, enable direct communication between neural tissue and electronic systems. The goal of this research is to restore lost sensory or motor functions, treat neurological disorders, or enhance human capabilities. Neural interface research is highly interdisciplinary, involving neuroscience, engineering, computer science, and medicine. Advances in this field have the potential to revolutionize healthcare and human-machine interaction.

What are the key skills and qualifications needed to thrive in neural interface research?

To thrive in Neural Interface Research, you need advanced knowledge in neuroscience, biomedical engineering, and signal processing, often supported by a graduate degree in a related field. Proficiency with programming languages (such as Python or MATLAB), neural data acquisition systems, and simulation tools is typically required. Exceptional problem-solving abilities, collaboration, and strong communication skills help researchers innovate and translate findings across multidisciplinary teams. These skills are crucial for developing cutting-edge neural technologies and ensuring rigorous, impactful scientific progress.

What are some common interdisciplinary challenges faced by professionals in neural interface research teams?

Neural Interface Research teams often bring together experts from neuroscience, engineering, computer science, and clinical backgrounds, which can lead to challenges in communication and aligning goals across disciplines. Collaborators may use different terminology or have varying expectations regarding project timelines and outcomes. Successful professionals in this field need to be proactive in fostering clear communication, demonstrating adaptability, and developing a basic understanding of adjacent fields to effectively contribute to collaborative projects. These interdisciplinary challenges ultimately offer valuable opportunities for personal growth and innovation.

What is the difference between Neural Interface Research vs Neural Engineering?

AspectNeural Interface ResearchNeural Engineering
Required CredentialsAdvanced degrees in neuroscience, biomedical engineering, or related fieldsSimilar credentials, often with additional focus on device design and implementation
Work EnvironmentResearch labs, universities, biotech companiesResearch labs, medical device companies, clinical settings
Industry UsageFocuses on developing and understanding neural interfacesDesigning, testing, and applying neural interface devices
Common Search IntentResearch methods, latest advancements, academic rolesProduct development, device engineering, clinical applications

Neural Interface Research primarily involves exploring and understanding neural interfaces through scientific investigation, while Neural Engineering focuses on designing and developing neural interface devices for practical use. Both roles require similar educational backgrounds but differ in their application and work environment.

What are popular job titles related to Neural Interface Research jobs in California?

For Neural Interface Research jobs in California, the most frequently searched job titles are:

What job categories do people searching Neural Interface Research jobs in California look for?

The top searched job categories for Neural Interface Research jobs in California are:

What cities in California are hiring for Neural Interface Research jobs?

Cities in California with the most Neural Interface Research job openings:

Neural Interface Research jobs near you
Infographic showing various Neural Interface Research job openings in California as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 87% Full Time, 9% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

On-Device Research Engineer

Hark

San Jose, CA • On-site

$120K - $300K/yr

Full-time

Re-posted 7 days ago

Job description

About Hark
Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory.
We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world.
To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems.
About the Role
We are looking for an On-Device Research Engineer to compress large audio and multimodal models into student models that meet the size, latency, and power budgets of our shipping hardware. This role sits between training and production. You will take teacher models from our research pipeline and produce student models that run on DSP, NPU, and microcontroller targets across our product line. You will own distillation, quantization, and architecture-aware compression as a first-class work-stream.
Responsibilities
  • Design and execute distillation strategies (response, feature, and self-distillation) to compress teacher models into deployable students
  • Apply quantization (PTQ and QAT), pruning, and architecture search to hit per-product size, latency, and power budgets
  • Build a reusable distillation and compression toolchain that the broader audio ML team can adopt across model families
  • Partner with the broader audio ML team on training pipelines and with the runtime team on deployment targets
  • Define accuracy retention and resource KPIs per product and track them through the release cycle
  • Profile compressed models on target hardware and iterate with DSP and runtime engineers on bottlenecks

Requirements
  • 3+ years of professional experience in model compression, distillation, quantization, or efficient deep learning
  • Strong fluency in PyTorch or TensorFlow and modern compression libraries
  • Hands-on experience taking models from full precision to fixed-point or int8 with controlled accuracy loss
  • Comfort working close to hardware and reasoning about compute, memory bandwidth, and power as design constraints
  • Track record of producing models that have shipped to constrained devices
  • Solid foundation in audio or sequence model architectures (CNNs, transformers, RNN-T, conformers)

Bonus Qualifications
  • Experience with Hexagon DSP, NPUs, Ambiq class MCUs, or similar
  • Experience with knowledge distillation at scale, including teacher-ensemble or multi-stage distillation
  • Familiarity with neural architecture search and hardware-aware NAS
  • Background shipping voice-first or far-field audio products
  • Contributions to open-source compression toolchains (TFLite, ONNX Runtime, AIMET, and similar)

Compensation
The US base salary range for this full-time position is between $120,000 - $300,000 annually.
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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