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Neural Interface Engineer Jobs in Ashburn, VA (NOW HIRING)

Lead Bioengineer

Ashburn, VA · On-site

$145 - $165/hr

... neural substrate of the CEREBRION bionic brain in both its living and engineered, materials‑based forms; the bioelectronic interface that couples that substrate to the rest of the system; and all ...

Role Summary You will own the neural substrate of the CEREBRION bionic brain system in both its living and engineered, materials-based forms, as well as the bioelectronic interface that couples that ...

Modify existing software to correct errors, to adapt it to new hardware, or to upgrade interfaces ... Familiarity with machine learning algorithms and tools such as naïve-bayes, decision trees, neural ...

Lead Photonics Engineer

Ashburn, VA · On-site

$150K - $170K/yr

Key Responsibilities Photonics Engineering • Design and simulate photonic circuits, waveguides ... interfaces or neural probes. • Advanced research lab or deep-tech startup experience. A ...

Develop and maintain user-friendly AI applications and interfaces, including chatbots, virtual ... Solid understanding of deep learning architectures such as CNNs (Convolutional Neural Networks ...

Develop and maintain user-friendly AI applications and interfaces, including chatbots, virtual ... Solid understanding of deep learning architectures such as CNNs (Convolutional Neural Networks ...

Develop and maintain user-friendly AI applications and interfaces, including chatbots, virtual ... Solid understanding of deep learning architectures such as CNNs (Convolutional Neural Networks ...

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Showing results 1-20

Neural Interface Engineer information

See Ashburn, VA salary details

$11.2K

$108.8K

$217.3K

How much do neural interface engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for neural interface engineer in Ashburn, VA is $108,838.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,900.00 and $209,600.00 per year, depending on experience, location, and employer.

What is the difference between Neural Interface Engineer vs Brain-Computer Interface Developer?

AspectNeural Interface EngineerBrain-Computer Interface Developer
Required CredentialsBachelor's or Master's in Neuroscience, Biomedical Engineering, or related fieldsBachelor's or Master's in Computer Science, Neuroscience, or Biomedical Engineering
Work EnvironmentResearch labs, medical device companies, biotech firmsTech startups, research institutions, healthcare companies
Industry UsageDevelops hardware/software for neural data acquisition and processingDesigns algorithms and interfaces for translating neural signals into commands
Common Search/ComparisonOften compared due to overlapping skills in neural data and hardware developmentRelated but more software-focused

Neural Interface Engineers focus on developing hardware and systems to connect the nervous system with external devices, while Brain-Computer Interface Developers primarily design software algorithms to interpret neural signals. Both roles require knowledge of neuroscience and engineering, but differ in their emphasis on hardware versus software development.

What are popular job titles related to Neural Interface Engineer jobs in Ashburn, VA?

For Neural Interface Engineer jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Neural Interface Engineer jobs in Ashburn, VA look for?

The top searched job categories for Neural Interface Engineer jobs in Ashburn, VA are:

What cities near Ashburn, VA are hiring for Neural Interface Engineer jobs?

Cities near Ashburn, VA with the most Neural Interface Engineer job openings:

Lead Bioengineer

Devyantram

Ashburn, VA • On-site

$145 - $165/hr

Other

Posted 4 days ago


Job description

Devyantram is building a unified platform of bionic robots, from nanoscale to humanoid, powered by a bionic brain system that fuses biotechnology, nanotechnology, and AI to tackle global challenges in climate, medicine, and defense.

Role Summary

You will own the living‑systems layer of Devyantram's platform end to end: the neural substrate of the CEREBRION bionic brain in both its living and engineered, materials‑based forms; the bioelectronic interface that couples that substrate to the rest of the system; and all biological and living‑material aspects of the platform, including regenerative and self‑healing systems. You define how living and engineered substrates combine into adaptive, learning, durable embodiments, working closely with the photonics, mechatronics, and controls leads on integration.

Key Responsibilities
  • Own the neural substrate of CEREBRION across both its living and engineered, materials‑based forms.
  • Develop and maintain engineered neural tissue and biohybrid substrates.
  • Design and build materials‑based, neural‑emulating substrates using ionic and conducting‑polymer (iontronic) device approaches.
  • Partner with the photonics and micro/nano lead on the device‑level fabrication and physics of materials‑based substrates.
  • Support closed‑loop learning across the integrated system.
  • Establish biosafety, ethics, and reproducibility standards for all living‑systems work.
Bioelectronic Interface
  • Own the bioelectronic interface between biological substrates and the platform's electronic and optical subsystems.
  • Develop and characterize the interface materials and transduction approaches that make that coupling reliable.
  • Collaborate with the photonics and controls leads on integration across the interface.
  • Engineer regenerative and bio‑hybrid materials for robotic systems, including self‑healing skins, scaffolds, and adaptive structural elements.
  • Develop repair and regeneration pathways for long‑lived, damage‑tolerant embodiments.
  • Design and engineer functional polymers, hydrogels, and soft‑matter systems for interfacing, actuation, sensing, and structural use.
  • Develop stimuli‑responsive and adaptive materials across electrical, optical, chemical, and mechanical domains.
  • Explore molecular‑scale and programmable‑matter approaches to local sensing and actuation.
  • Support integration of these systems with the broader micro and nano platform.
IP & Technical Leadership
  • Generate foundational IP across neural and biohybrid systems, ionic and organic‑bioelectronic devices, bioelectronic interfaces, and living and regenerative materials.
  • Lead invention disclosures and experimental validation in coordination with patent counsel.
  • Build and mentor the wet‑lab and bioengineering team over time.
Required Qualifications
  • MS or PhD in Bioengineering, Neural Engineering, Biomedical Engineering, or a related field (Neuroscience, Synthetic Biology, or Materials Science with a bioelectronics focus are all relevant).
  • 8+ years of hands‑on research and development experience across living‑systems and bioelectronic work.
  • A strong living‑systems foundation spanning engineered neural tissue, biohybrid systems, and organoids, with demonstrated depth in at least one of these branches.
  • Firm requirement: hands‑on experience with bioelectronic interfaces, the coupling between neural or biological substrates and electronic or optical systems. This is the core of the role and the hardest part to outsource.
  • Experience with ionic and conducting‑polymer devices, iontronics, or organic bioelectronics, and the ability to build materials‑based, neural‑emulating substrates.
  • Demonstrated ability to take living or materials‑based systems from bench to integrated, reproducible use.
  • Strong experimental design and cross‑disciplinary communication.
Strongly Preferred
  • Organic bioelectronics, iontronics, or neuromorphic materials.
  • Organoid, neural‑tissue, or biohybrid‑computing research.
  • Bioelectronic interfaces, neural probes, or brain‑machine interfaces.
  • Regenerative medicine, tissue engineering, or self‑healing and stimuli‑responsive materials.
  • Molecular machines or programmable matter.
  • Experience bridging wet‑lab, hardware, and robotics teams.
A Successful Candidate Will Be Measured By
  • Stability, function, and learning capacity of the neural substrate across its living and engineered forms.
  • Reliability of the bioelectronic interface across the integrated system.
  • Performance and longevity of regenerative and self‑healing materials.
  • Successful integration of living‑systems work with the rest of the platform.
  • Strength and defensibility of generated biotech and materials IP.

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.

The pay range for this role is:

145,000 - 165,000 USD per year (Ashburn, VA)

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