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Internship Brain Machine Interface Jobs in Missouri

$16.92 - $26.44/hr

... interface of protein engineering, optical imaging, and systems neuroscience. The successful ... including machine learning-guided protein engineering. This position offers an excellent ...

Internship Brain Machine Interface information

What types of projects or tasks can I expect to work on during a brain machine interface internship?

As a Brain Machine Interface (BMI) intern, you'll typically assist with experimental design, data collection, and analysis involving neurophysiological signals, such as EEG or intracortical recordings. You may help develop or test algorithms for signal processing and decoding brain activity, or support the integration of hardware and software systems. Collaboration with neuroscientists, engineers, and software developers is common, so you’ll gain exposure to both research and technical development environments. Interns often have the opportunity to contribute to ongoing research publications or product development, which can be valuable experience for future roles.

What are the key skills and qualifications needed to thrive as an internship brain machine interface?

To thrive in a Brain Machine Interface internship, you typically need a background in neuroscience, biomedical engineering, computer science, or a related field, with coursework or experience in signal processing and neural data analysis. Familiarity with programming languages like Python or MATLAB, as well as experience with neural recording systems and data acquisition tools, is often required. Strong analytical thinking, problem-solving abilities, and effective communication skills help interns collaborate and contribute meaningfully to research teams. These skills enable interns to support innovative projects at the intersection of neuroscience and technology, ensuring they can learn quickly and add value to complex research environments.

What is an internship brain machine interface?

Internship Brain Machine Interface positions are short-term roles typically offered to students or recent graduates to gain hands-on experience working with brain-machine interface (BMI) technologies. These internships involve assisting with research, development, and testing of systems that connect the human brain to external devices, often in fields like neuroscience, biomedical engineering, or computer science. Interns may work on tasks such as data analysis, programming, hardware development, or conducting experiments under the supervision of experienced professionals. The goal is to provide practical exposure and skill development in cutting-edge neurotechnology.

What is the difference between Internship Brain Machine Interface vs Research Assistant in Brain-Computer Interface?

AspectInternship Brain Machine InterfaceResearch Assistant in Brain-Computer Interface
Required CredentialsEnrolled in relevant undergraduate or graduate programGraduate degree or ongoing research experience in neuroscience or engineering
Work EnvironmentInternship setting, often in labs or tech companiesAcademic or research institution labs
Employer & Industry UsageTech companies, startups, research labsUniversities, research institutes, industry R&D
Common Search & Comparison IntentUnderstanding internship roles in BMIResearch roles in brain-computer interfaces

While both roles involve working with brain-machine interface technology, an Internship Brain Machine Interface typically targets students gaining initial industry experience, whereas a Research Assistant in Brain-Computer Interface usually involves more advanced research responsibilities within academic or research institutions.

What are popular job titles related to Internship Brain Machine Interface jobs in Missouri? For Internship Brain Machine Interface jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Internship Brain Machine Interface jobs in Missouri look for? The top searched job categories for Internship Brain Machine Interface jobs in Missouri are:
What cities in Missouri are hiring for Internship Brain Machine Interface jobs? Cities in Missouri with the most Internship Brain Machine Interface job openings:
Infographic showing various Internship Brain Machine Interface job openings in Missouri as of August 2026, with employment types broken down into 82% Full Time, 11% Part Time, 5% Contract, and 2% Nights. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution.

Staff/Principal Machine Learning Engineer

Socket.dev

California, MO • On-site

$180 - $280/hr

Other

Medical, PTO

Posted 6 days ago


Job description

About Us

Epia Neuro is a neural technology company developing intent-driven systems that restore function and independence for people living with neurological conditions. Our platform integrates implantable neural interfaces, adaptive algorithms, and assistive devices to translate neural intent into real-world action. Our initial focus is stroke-related motor impairment, with planned expansion into cognitive decline and other neurological disorders.

The Role

We have a strong research group driving early brain-computer-interface (BCI) algorithm development. We are looking for someone with deep, hands-on BCI machine learning (ML) expertise to own neural decoding and carry it from validated research approaches to real-time algorithms running in human clinical studies. This is where applied BCI work gets real: your models decode intent from actual participants, under the constraints of a live clinical program.

This is a senior individual-contributor leadership role, open at the Staff or Principal level depending on skills and experience. You will set ML technical strategy across decoder design, the decoding platform, and system architecture. Your focus is neural decoding, but your influence won\u2019t stop there: you will help raise the bar for ML engineering and modeling practices across the company. You will stay hands-on, working closely with our research team and with Software, Firmware, Hardware, and Robotics.

How We Work
  • We are intentional. We prioritize and are thoughtful about how we use others\' time.

  • We care for others. We prioritize safety both for patients and one another.

  • We own outcomes, not just tasks. Our work demands the highest standards because it impacts real patients and real lives.

  • Humility is a strength. We are honest about what we know and what we don\'t know. Getting it right matters more than being right.

Location

This role is based out of the San Francisco Bay Area and expected to work on site from our Alameda headquarters 2–3 days a week.

Key Responsibilities

Technical Direction and Strategy

  • Own ML technical strategy for neural decoding, from validated approaches through real-time algorithms deployed in human clinical studies, spanning decoder design, the decoding platform, and system architecture.

  • Define data collection, labeling, and evaluation protocols for neural and behavioral data, and set performance criteria tied to clinical use.

  • Contribute to long-term BCI and machine learning platform strategy.

Decoding and Deployment

  • Partner with our research team to take neural decoding approaches from concept through validated prototype, including model design, training, and evaluation.

  • Develop and improve real-time, closed-loop decoding of neural intent, including online calibration, decoder adaptation, and robustness over time.

  • Own productization of the decoding algorithms, taking validated approaches to a deployable real-time inference runtime that meets latency and power budgets on the device.

  • Own integration of decoding models into the broader medical device product across Software, Firmware, Hardware, and Robotics.

  • Lead the ML side of human clinical study deployment, accounting for signal non-stationarity, session-to-session variability, limited participant time, and clinical-trial safety and regulatory constraints.

  • Lead debugging and root-cause analysis across the ML, firmware, and controls boundaries.

Standards and Cross-Functional Leadership
  • Set ML engineering standards, documentation practices, and test methodologies within our regulated software lifecycle, and review the work of other engineers against them.

  • Mentor engineers across the ML function and strengthen the team\'s technical depth.

  • Represent ML technical positions in regulatory strategy, partner discussions, and work with scientific advisors.

Qualifications
  • PhD in computational neuroscience, machine learning, or a related field is expected.

  • 4-8+ years developing and deploying BCI algorithms in an industry or product setting, with a track record of owning technical direction at a scope that spans teams.

  • Production-quality Python and strong software engineering fundamentals, including testing, code review, and maintainable design in a collaborative codebase.

  • Deep expertise in neural signal processing and real-time, closed-loop decoding, calibration, and adaptation.

  • A working understanding of the practical constraints and failure modes of real BCI clinical trials.

  • Excellent communication and cross-functional collaboration skills.

Preferred Qualifications
  • Direct experience leading neural decoding through an end-to-end human clinical deployment.

  • PhD or postdoctoral training in a leading neural prosthetics, motor systems, or BCI research lab.

  • Proficiency in C++ or embedded development for an inference runtime, and edge or on-device ML.

  • Familiarity with safety-critical or regulated systems, such as medical devices (IEC 62304, ISO 13485, design controls).

Physical Requirements

Ability to work on site in a lab environment, including participating in hands-on data collection and bench testing with prototype hardware. Requires manual dexterity for handling devices, some standing during test and integration sessions, and the ability to safely operate lab equipment.

Benefits

Full-time employees are eligible for the following benefits listed below.

  • Competitive base salary with equity

  • 100% of healthcare coverage for you and your dependents

  • Generous vacation policy

  • Paid parental leave

  • Work from our beautiful waterfront office in Alameda, CA, with access to collaborative spaces and labs.

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