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Neural Interface Engineer Jobs in North Carolina

Neural Interface Engineer information

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.

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$40/hr

Full-time

Re-posted 19 days ago


Job description

JOB SUMMARY

We are building an AI-first company - which means AI isn't a feature we bolt on; it's the foundation of how we design products, make decisions, and ship software. As an Associate AI/ML Full Stack Developer, you'll be on the front lines of that mission: building intelligent, production-ready applications that put machine learning at the core of the user experience.

This is a role for someone who wants to grow fast. You'll work alongside experienced engineers and data scientists on real problems, ship code that matters, and develop deep expertise at the intersection of AI/ML and full stack development - all in service of one of the most consequential industries in the world.

Key Responsibilities:
  • Build and ship AI-powered full stack applications - from model integration to user-facing interfaces - using modern frameworks and cloud-native infrastructure.
  • Partner with data scientists to bring ML models into production: wrapping them in APIs, optimizing inference pipelines, and monitoring performance in live environments.
  • Own end-to-end data pipelines that support model training, validation, and deployment workflows.
  • Develop frontend experiences (React or similar) that surface AI-driven insights in intuitive, responsive interfaces.
  • Contribute to backend services and microservices that power model serving, data ingestion, and business logic.
  • Participate in code reviews and collaborative design discussions - learning from senior engineers while sharing your own perspective.
  • Stay current with the AI/ML landscape: new architectures, tooling, and frameworks move fast, and so do we.
What you'll need:

Required:

  • Bachelor's degree in Computer Science or a related technical field (or equivalent practical experience).
  • Solid grounding in data structures, algorithms, and object-oriented programming.
  • Understanding of core AI/ML concepts: supervised and unsupervised learning, neural networks, model evaluation.
  • Proficiency in at least one backend language - Python strongly preferred given its centrality to the ML ecosystem.
  • Hands-on experience with web development (React, Angular, or comparable framework).
  • Comfort with both SQL and NoSQL databases.
  • A problem-solving mindset and genuine curiosity about how AI can change the way software works.

Nice to Have:

  • Experience with Python ML libraries: TensorFlow, PyTorch, or Scikit-learn.
  • Familiarity with cloud platforms (AWS, GCP, or Azure) and deploying ML workloads in the cloud.
  • Exposure to LLM APIs, prompt engineering, or retrieval-augmented generation (RAG) patterns.
  • Knowledge of MLOps tooling: experiment tracking, model registries, CI/CD for ML pipelines.
  • Project or coursework experience building AI/ML applications end-to-end.

Who you are:

  • You think AI-first - when approaching a problem, your instinct is to ask how intelligence can be built into the solution, not added as an afterthought.
  • You move fast and learn faster. You're comfortable with ambiguity and excited by the pace of change in the AI space.
  • You communicate clearly and collaborate naturally across disciplines - you can talk to a data scientist about model architecture and to a product manager about tradeoffs.
  • You take ownership. You don't wait to be told what to do next; you find the next important thing and work on it.
  • You care about craft - clean code, thoughtful documentation, and systems that are built to last.

Base Compensation: $40/hr