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Neural Interface Research Jobs in Texas (NOW HIRING)

You will have access to the most cutting-edge neural interface hardware and develop ... Formulate research questions to guide the development of neural networks and signal processing ...

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

You will have access to the most cutting-edge neural interface hardware and develop ... Formulate research questions to guide the development of neural networks and signal processing ...

... of neural interface technology. Key Responsibilities: * Technical Acquisition: Execute complex ... Research Mindset: Comfort working with both human participants and veterinary subjects in a fast ...

Gen AI Lead - TX

Irving, TX

$15.50 - $18.75/hr

... Neural Network models, and Vector/Graph Databases (Pinecone, Milvus, Neo4j). * Oversee the ... Stay at the forefront of Gen AI research, actively exploring new tools, frameworks (Langchain ...

Gen AI Lead - TX

Irving, TX · On-site

$15.50 - $18.75/hr

... Neural Network models, and Vector/Graph Databases (Pinecone, Milvus, Neo4j). * Oversee the ... Stay at the forefront of Gen AI research, actively exploring new tools, frameworks (Langchain ...

IACUC Coordinator

Austin, TX · On-site

$19.50 - $24.75/hr

... research activities supporting the development of Neuralink's brain-machine interfaces ... Background in neuroscience, neural device studies, or GLP-regulated preclinical research.

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Neural Interface Research information

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 the key skills and qualifications needed to thrive in Neural Interface Research, and why are they important?

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 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 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 cities in Texas are hiring for Neural Interface Research jobs? Cities in Texas with the most Neural Interface Research job openings:
Infographic showing various Neural Interface Research job openings in Texas as of July 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.

Machine Learning Engineer

Neuralink

Austin, TX

Other

Re-posted 23 days ago


Job description

About the Team:

The BCI team develops the software and systems that communicate with the brain. These systems decode raw neural signals into useful actions, such as moving a cursor, typing, or actuating a robotic arm. Additionally, real-world data, such as video feeds, can be encoded into neural data to project images into the visual cortex. We also work closely with users to gather feedback, make improvements, and fundamentally reshape the user experience and interface of the BCI.

About the Role:

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. 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 solutions grounded in first principles.

Neuralink designs all hardware in-house, from custom ASICs to thin-film arrays. There is no part of the technical design that cannot change. Learnings from your work will directly influence next-generation device architecture.

Job Responsibilities:
  • Telepathy Product: Develop and refine models that decode neural data, enabling individuals with paralysis to reliably type at 35 words per minute or control robotics arms for activities of daily living.
  • Blindsight Product: Formulate research questions to guide the development of neural networks and signal processing algorithms that will restore vision to those affected by blindness.
  • Utilize your fundamental understanding of neural networks and data science to develop models that serve as the foundation for machine learning applications for BCI.
  • Lead the team by performing at a high standard, setting the bar for how we build and operate our systems.
  • Inform our hardware roadmap by understanding users and identifying the product features that would have the greatest impact on their quality of life.
About You:
  • Experience writing production-level C/C++/Rust and Python
  • Proven track record of designing, building, and shipping real-time ML products
  • Strong foundation in signal processing, algorithms, and software engineering principles
  • Bachelor's degree in relevant field or equivalent experience

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