1

Neural Engineering Jobs in Washington (NOW HIRING)

AI Engineer

MD · On-site

$80K - $160K/yr

Develop Convolutional Neural Networks and GANs * Develop various prototypes for synthetic data, cybersecurity, digital engineering, remote sensing, and other emerging areas * Conduct model training ...

Bachelor's degree in computer science, Information Technology Management or Engineering is ... Solid understanding of deep learning architectures such as CNNs (Convolutional Neural Networks ...

Showing results 41-60

Neural Engineering information

See Washington salary details

$12

$21

$33

How much do neural engineering jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for neural engineering in Washington is $21.88, according to ZipRecruiter salary data. Most workers in this role earn between $18.22 and $23.70 per hour, depending on experience, location, and employer.

What is neural engineering?

Neural engineering is a multidisciplinary field that combines engineering, neuroscience, and computational approaches to understand, repair, enhance, or interface with the nervous system. Neural engineers develop devices such as brain-computer interfaces, neural prosthetics, and neurostimulation systems to restore or improve neural function. This field plays an important role in advancing treatments for neurological disorders and in creating technologies that bridge the gap between machines and the human brain.

What are the key skills and qualifications needed to thrive as a neural engineer, and why are they important?

To thrive as a Neural Engineer, you need a strong background in neuroscience, biomedical engineering, and signal processing, typically supported by an advanced degree in a related field. Familiarity with programming languages (such as MATLAB or Python), neuroimaging tools, and hardware platforms used for neural interfacing is essential. Excellent problem-solving skills, collaboration, and clear communication set standout professionals apart in this multidisciplinary environment. These skills are crucial for developing innovative neural technologies and translating research into effective clinical or commercial solutions.

Is neural engineering a good career?

Neural engineering is a growing interdisciplinary field that combines neuroscience, engineering, and computer science to develop technologies like brain-computer interfaces and neural prosthetics. It offers opportunities in research, healthcare, and industry, often requiring advanced degrees and technical skills. The field is expected to expand as neurotechnology advances and healthcare needs increase.

What can you do with a neural engineering degree?

A neural engineering degree prepares individuals for careers in developing brain-computer interfaces, neuroprosthetics, and neural signal processing. Graduates often work in research, healthcare, or technology companies, utilizing skills in neuroscience, engineering, and programming to innovate medical devices and neural systems.

What are jobs in neural engineering?

Jobs in neural engineering focus on helping research and design biomedical devices like prosthetic limbs and artificial organs. In these roles, you may determine the best way to implement designs for each situation, figure out the best way to link mechanical systems to the human brain, and find the most cost-effective ways to build devices. Neural engineering differs from engineering regular prosthetic limbs in that they receive instructions directly from the brain and often send information back, rather than simply being attached to the body. This often involves programming specialized software and figuring out how to make devices that can teach the brain how to use them. In recent years, neural engineering has started to move out of the medical realm, and there may be more jobs of that nature in the future. Neural engineering is a specific type of biomedical engineering, but should not be confused with jobs in the broader category.

What are some common interdisciplinary challenges faced by neural engineers when collaborating with clinicians and data scientists?

Neural engineers frequently work on teams that include clinicians, data scientists, and hardware specialists, which can present unique interdisciplinary challenges. Effective communication is essential, as team members often have different technical backgrounds and priorities—clinicians focus on patient outcomes, while data scientists emphasize analytical accuracy. Bridging the gap between clinical needs and technical feasibility requires adaptability, openness to feedback, and a willingness to learn new concepts. Building strong collaborative relationships and participating in regular cross-functional meetings can help ensure that project goals are clearly understood and met by all stakeholders.

What are the most commonly searched types of Neural Engineering jobs in Washington?

The most popular types of Neural Engineering jobs in Washington are:

What are popular job titles related to Neural Engineering jobs in Washington?

For Neural Engineering jobs in Washington, the most frequently searched job titles are:

What cities in Washington are hiring for Neural Engineering jobs?

Cities in Washington with the most Neural Engineering job openings:

Infographic showing various Neural Engineering job openings in Washington as of July 2026, with employment types broken down into 89% Full Time, 6% Part Time, 4% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $45,501 per year, or $21.9 per hour.

Artificial Intelligence / Machine Learning Data Engineer with Security Clearance

MAG DS Corp dba MAG Aerospace

Fairfax, VA • On-site

$117K - $140K/yr

Other

Re-posted 19 days ago


Job description

Position Summary MAG Aerospace is staffing for a Artificial Intelligence / Machine Learning Data Engineer. This position will l ead the development of intelligent systems that transform multi-modal sensor data into actionable intelligence for tactical operations. You'll leverage COTS, FOSS/OSS, and custom development to build or integrate everything from edge computer vision to conversational AI assistants, while managing the data pipelines that feed these systems in the most challenging environments. While you'll have a core expertise in either data engineering or model development, you have a passion for mastering the full stack of AI systems. US Citizens Only Former US Defense Contractor / US Gov / US Military Experience Only This is a Hybrid Position - Remote mainly - but as well on call to come into a MAG office when requested We are seeking candidates who live in proximity to our corporate HQ in Fairfax, VA primarily but will entertain persons living near our satellite offices in: Aberdeen, MD - Titusville, FL - Newport News, VA - Carthage NC Essential Duties and Responsibilities Duties include, but not limited to: Primary Responsibilities: * Develop and optimize data-centric AI solutions such as computer vision pipelines for object detection, tracking, and classification * Implement advanced AI capabilities including RAG systems, agentic workflows, and fine-tuned LLMs * Design and deploy edge-optimized models using TensorRT, ONNX, and quantization techniques * Build data engineering pipelines for ETL, feature engineering, and model training * Create analytics dashboards and business intelligence solutions for operational insights * Implement multi-modal sensor fusion algorithms (visual, thermal, acoustic, RF) * Design and maintain data lakes, warehouses, and real-time streaming architectures * Develop conversational AI interfaces using open-source LLMs (Llama, Mistral, etc.) * Establish and enforce data quality standards, validation checks, and governance procedures throughout the data lifecycle * Develop and implement robust testing and validation strategies for AI/ML models, including performance under degraded data conditions, adversarial testing, and operational scenarios Secondary Responsibilities: * Optimize AI workloads for embedded platforms (Jetson, Intel Neural Compute Stick) * Implement hardware acceleration using CUDA and TensorRT * Profile and optimize memory/power consumption for edge devices * Support embedded systems team with AI-specific hardware integration * Design distributed inference systems for degraded network conditions Requirements Minimum Requirements: Primary Experience / Qualifications: * 5+ years' experience in machine learning, AI, and data engineering * Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX) * Experience with modern AI paradigms (transformers, diffusion models, neural ODEs) * Hands-on experience with LLM deployment and optimization (vLLM, TGI, llama.cpp) * Proficiency with data engineering tools (Apache Spark, Airflow, dbt, etc.) * Experience with both SQL and NoSQL databases at scale * Knowledge of vector databases and embedding systems (Pinecone, Weaviate, pgvector) * Experience with computer vision libraries (OpenCV, PIL) and video processing * Understanding of MLOps practices and model lifecycle management Preferred Qualifications * Experience with military/defense AI applications * Knowledge of agentic AI frameworks (LangChain, AutoGPT, CrewAI) * Familiarity with federated learning and edge-cloud hybrid architectures * Experience with business intelligence tools (Tableau, PowerBI, Grafana) * Knowledge of time-series analysis and anomaly detection * Experience with knowledge graphs and semantic reasoning * Understanding of explainable AI and model interpretability * Experience with MLOps platforms and tools (e.g., MLflow, Kubeflow, Weights & Biases) * Published research or patents in relevant areas Education & Experience: * Bachelor's degree in CS, EE, or related field; * Master's preferred Clearance: * Must be eligible for Secret security clearance Other Qualifications: * Must be a US citizen Special Note What Makes You Successful Here * You can build anything from a computer vision pipeline to a conversational AI assistant * You treat data engineering as seriously as model development * You understand the tradeoffs between cloud-scale and edge deployment * You can explain complex AI concepts to operators and executives alike * You see AI as a tool for augmenting human decision-making, not replacing it Why Join MAG: * Work on meaningful problems that directly impact national security * Small, elite team where your contributions matter immediately * Access to cutting-edge hardware and technologies * Rapid prototyping environment - see your ideas deployed in weeks * Direct interaction with end users and field deployments * Professional development and conference attendance support * Flexible work arrangements with occasional field exercises * Opportunity to shape the future of tactical edge computing Company Policy MAG Aerospace (MAG) is an Equal Opportunity/Affirmative Action Employer and is committed to Diversity and Inclusion. We encourage diverse candidates to apply to our positions. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Click below for the "EEO is The Law" and "Pay Transparency Nondiscrimination" supplement posters. https://www.dol.gov/agencies/ofccp/posters MAG Aerospace (MAG) is committed to providing an online application process that is accessible to all, including individuals with a disability, by offering an alternative way to apply for job openings. This alternative method is available for those who cannot otherwise complete the online application due to a disability or need for accommodation. MAG provides reasonable accommodation to applicants under the guidance of the Americans with Disabilities Act (ADA), Section 503 of the Rehabilitation Act of 1973, the Vietnam-Era Veterans' Readjustment Assistance Act of 1974, and certain state and/or local laws. If you need assistance due to a disability, please contact the MAG Aerospace Recruiting email: or call (703) 376-8993.