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Neural Interface Jobs (NOW HIRING)

Neuralink

Machine Learning Engineer

Austin, TX · On-site

You will have access to the most cutting-edge neural interface hardware and develop state-of-the-art neural encoders and decoders. No prior knowledge of neuroscience is required; we value simple ...

Delsys

R&D Software Engineer (Intern)

Natick, MA · On-site

$28 - $34/hr

Delsys R&D Software Engineers collaborate with engineers and scientists to solve challenges spanning the fields of movement science & human health, including the development of neural interface ...

Neuralink

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

You will have access to the most cutting-edge neural interface hardware and develop state-of-the-art neural encoders and decoders. No prior knowledge of neuroscience is required; we value simple ...

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How much do neural interface jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for neural interface in the United States is $54.94, according to ZipRecruiter salary data. Most workers in this role earn between $48.08 and $62.50 per hour, depending on experience, location, and employer.

What is a neural interface?

Neural interfaces are devices or systems that enable direct communication between the brain or nervous system and external technology, such as computers or prosthetics. They can be used to restore lost sensory or motor functions, assist with medical diagnostics, or even enhance human capabilities. Neural interfaces work by detecting and interpreting electrical signals from neurons, then translating them into commands for external devices, or vice versa. This technology is advancing rapidly and holds promise for applications in healthcare, neuroscience research, and brain-computer interaction.

What skills and qualifications are needed to work in neural interface?

To thrive as a Neural Interface Engineer, you need expertise in neuroscience, bioengineering, signal processing, and a related advanced degree such as in biomedical engineering or electrical engineering. Proficiency with neural recording hardware, software for data analysis (like MATLAB or Python), and familiarity with regulatory standards are typically required. Strong problem-solving, attention to detail, and collaborative communication skills help drive innovation and ensure safety in multidisciplinary teams. These skills are crucial for developing reliable neural interface technologies that can safely interact with the nervous system and advance both clinical and research applications.

What are common challenges in neural interface development and how can they be addressed?

Professionals in neural interface development often encounter challenges such as integrating biological systems with electronic devices, ensuring long-term stability and biocompatibility, and addressing ethical considerations related to data privacy and user safety. Collaborating closely with multidisciplinary teams—including neuroscientists, engineers, and clinicians—can help address these difficulties by bringing diverse perspectives and expertise. Staying updated with the latest research and adhering to rigorous testing protocols are also essential for success in this rapidly evolving field.

What is the difference between Neural Interface vs Neural Engineer?

AspectNeural InterfaceNeural Engineer
Required CredentialsTypically requires a background in neuroscience, biomedical engineering, or related fields; certifications varyRequires a degree in biomedical engineering, electrical engineering, or neuroscience; often includes certifications in related technologies
Work EnvironmentResearch labs, medical device companies, or tech firms focusing on brain-computer interfacesResearch institutions, tech companies, or healthcare organizations developing neural technologies
Industry UsageDesigning, testing, or implementing neural interface devices and systemsDeveloping neural interface hardware/software, improving signal processing, and system integration

Neural Interface professionals focus on the development and application of devices that connect the brain to external systems, while Neural Engineers design and improve these systems, often working on the hardware and software aspects. Both roles overlap in skills and industry but differ in their primary focus and responsibilities.

Software Engineering Manager - Neural Interface ML Infra

Meta

Bellevue, WA

$184K/yr

Full-time

Posted 22 days ago

Key responsibilities

  • Drive complex hardware-software co-design projects to completion, managing roadmaps, timelines, and risk mitigation.

  • Collaborate with cross-functional teams including AI Infra, Hardware Engineering, Product, and Research to support neural interface ML infrastructure.

  • Engage in technical design reviews, architecture decisions, and define technical vision with Tech Leads.

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

139th of 247 rated software companies

Job description

Lead a team at the intersection of AI, distributed systems, and hardware architecture. The role drives ML model efficiency and scalability, infrastructure costs, and enables embedded AI capabilities. Directly supporting Meta's ability to train and serve AI models for wearable products.
Software Engineering Manager - Neural Interface ML Infra Responsibilities:
  • People Leadership: Build/retain an engineering team
  • provide coaching, mentorship, and performance management
  • Technical Leadership: Engage in design reviews, architecture decisions, and technical trade-offs
  • define technical vision with Tech Leads
  • Execution: Drive complex hardware-software co-design projects to completion
  • manage roadmaps, timelines, and risk mitigation
  • Cross-Functional Partnership: Collaborate with AI Infra, Hardware Engineering, Product, and Research
  • represent the team to leadership

Minimum Qualifications:
  • 3+ years managing software engineering teams with a track record of delivering measurable outcomes
  • Technical background in at least two of: AI/ML systems, distributed/HPC systems, software tooling and infrastructure or model optimization with GPUs/accelerators
  • Demonstrated ability to engage deep in technical work and guide decisions
  • Proven track record growing engineers
  • Experience communicating technical strategy and influencing cross-functional stakeholders through written proposals and presentations

Preferred Qualifications:
  • M.S. or Ph.D. in CS, EE, or related field
  • Prior Tech Lead, TLM, or IC experience before management
  • Experience building teams in ambiguous, exploratory domains
  • Track record of maintaining team engagement, retention, and consistent delivery outcomes
  • Experience managing AI infrastructure and capacity including GPU/CPU used for training, benchmarking and inference
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience with PyTorch, TensorFlow, or equivalent AI frameworks
  • Familiarity with AI compilers, high-performance kernel development, or hardware enablement
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Background in performance optimization/profiling
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$184,000/year to $257,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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