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Remote Brain Computer Interface Jobs in Alabama (NOW HIRING)

Huntington

Sr. Innovation Software Engineer

Birmingham, AL · On-site +1

$114K - $151K/yr

Design and implement APIs, backend services, workflow automations, and UI experiences to support ... Bachelor's degree in Computer Science, Information Technology, Engineering or a related technical ...

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Remote Brain Computer Interface information

What are the key skills and qualifications needed to thrive as a Remote Brain Computer Interface (BCI) Engineer, and why are they important?

To thrive as a Remote Brain Computer Interface Engineer, you need expertise in neuroscience, signal processing, software development, and ideally an advanced degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages (such as Python or MATLAB), BCI platforms (like OpenBCI), and experience with EEG/EMG systems are typically required. Strong problem-solving skills, attention to detail, and effective remote communication abilities set candidates apart. These skills ensure the development and maintenance of robust BCI systems, successful remote collaboration, and the advancement of innovative neurotechnology solutions.

What are Remote Brain Computer Interface jobs?

Remote Brain Computer Interface (BCI) jobs involve designing, developing, testing, or supporting technologies that enable direct communication between the brain and external devices, all while working from a remote location. These roles can include research scientists, software engineers, data analysts, or user interface designers specializing in BCI applications. Professionals in this field collaborate virtually to advance neurotechnology, contribute to assistive devices, or improve human-computer interaction. Remote BCI jobs often require expertise in neuroscience, computer science, machine learning, and signal processing.

What are some common challenges faced by professionals working in remote Brain-Computer Interface (BCI) roles?

Professionals in remote BCI positions often encounter challenges such as maintaining effective collaboration with cross-disciplinary teams, managing sensitive data securely, and troubleshooting specialized hardware or software remotely. Since BCI projects typically involve neuroscientists, engineers, and software developers, clear communication and regular virtual meetings are essential for synchronizing progress. Additionally, remote work can make testing and debugging BCI devices more complex, requiring creative solutions and sometimes coordination with onsite staff or labs.
What are the most commonly searched types of Brain Computer Interface jobs in Alabama? The most popular types of Brain Computer Interface jobs in Alabama are:
What are popular job titles related to Remote Brain Computer Interface jobs in Alabama? For Remote Brain Computer Interface jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Remote Brain Computer Interface jobs in Alabama look for? The top searched job categories for Remote Brain Computer Interface jobs in Alabama are:
What cities in Alabama are hiring for Remote Brain Computer Interface jobs? Cities in Alabama with the most Remote Brain Computer Interface job openings:
Remote Brain Computer Interface jobs near you
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Huntsville, AL • On-site, Remote

Full-time

Posted 3 days ago

Job description

Overview
FTI Defense is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.
FTI Defense delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.
Responsibilities
  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

Education/Qualifications
Minimum Requirements:
  • Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.
  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

Preferred Qualifications:
  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

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