1

Eeg Neural Signal Processing Jobs in Nevada (NOW HIRING)

Sr AI/ML Engineer

Sparks, NV

$106K - $146K/yr

Develop signal processing, perception, and planning pipelines supporting MPC control loops. * Use ... Demonstrated ability to design and optimize generative AI models (e.g., transformers) and neural ...

Eeg Neural Signal Processing information

What are some common challenges faced when processing EEG neural signals, and how can professionals address them in their daily work?

One of the main challenges in EEG neural signal processing is dealing with noise and artifacts, such as those caused by eye movements or muscle activity, which can obscure the true neural signals. Professionals often use specialized filtering techniques and artifact rejection algorithms to clean the data before analysis. Additionally, interpreting the complex and high-dimensional EEG data requires a solid understanding of both neuroscience and advanced signal processing methods. Collaborating closely with neuroscientists, clinicians, and software engineers is crucial for refining analysis pipelines and ensuring meaningful results.

What is EEG neural signal processing?

EEG neural signal processing refers to the analysis and interpretation of electrical activity in the brain as recorded by electroencephalography (EEG). This process involves filtering, amplifying, and extracting meaningful features from the raw EEG signals to study brain function, diagnose neurological disorders, or develop brain-computer interfaces. Researchers and clinicians use various computational techniques to separate noise from actual brain signals, enabling a better understanding of brain activity and aiding in medical or research applications.

What are the key skills and qualifications needed to thrive as an EEG Neural Signal Processing specialist, and why are they important?

To thrive as an EEG Neural Signal Processing specialist, you need a solid background in neuroscience, signal processing, and programming, typically supported by a degree in biomedical engineering, neuroscience, or related fields. Familiarity with technical tools such as MATLAB, Python, EEGLAB, and experience with EEG acquisition systems are essential. Strong analytical thinking, problem-solving skills, and clear communication help you interpret complex data and collaborate with interdisciplinary teams. These skills are crucial for accurately analyzing neural signals, advancing research, and ensuring reliable outcomes in clinical or research settings.

What is the difference between Eeg Neural Signal Processing vs Neurophysiologist?

AspectEeg Neural Signal ProcessingNeurophysiologist
Required CredentialsTypically requires a degree in neuroscience, biomedical engineering, or related fields; certifications in signal processing are a plusRequires advanced degrees (PhD or MD), specialized training in neurophysiology, and often board certification
Work EnvironmentResearch labs, hospitals, or tech companies focusing on brain signal analysisHospitals, clinics, research institutions conducting neurological assessments
Industry UsagePrimarily in research, medical device development, and data analysisClinical diagnosis, patient care, and neurological research

While Eeg Neural Signal Processing focuses on analyzing brain signals using signal processing techniques, Neurophysiologists perform clinical assessments and interpret neurological data. Both roles require a strong background in neuroscience, but neurophysiologists typically have more clinical responsibilities and advanced medical credentials.

What are popular job titles related to Eeg Neural Signal Processing jobs in Nevada? For Eeg Neural Signal Processing jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Eeg Neural Signal Processing jobs in Nevada look for? The top searched job categories for Eeg Neural Signal Processing jobs in Nevada are:
What cities in Nevada are hiring for Eeg Neural Signal Processing jobs? Cities in Nevada with the most Eeg Neural Signal Processing job openings:

$106K - $146K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 24 days ago


Sierra Nevada Corporation rating

8.7

Company rating: 8.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

17th of 71 rated aerospace companies


Job description

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading the development of complex AI/ML systems, driving innovation, and mentoring team members to deliver impactful solutions. In this role, you will oversee the design, implementation, and deployment of scalable AI/ML models for mission-critical aerospace and defense applications. You will also act as a technical leader, providing strategic guidance on AI/ML initiatives, ensuring compliance with regulatory standards, and collaborating with stakeholders to meet organizational objectives. This position demands advanced technical expertise and the ability to manage high-impact projects in a fast-paced environment.As SNC's corporate team, we provide the company and its business areas with strategic direction and business support spanning executive management, finance and accounting, operations, human resources, legal, IT, information security, facilities, marketing, and communications.

Responsibilities:

  • Exploration & Innovation:
    • Conduct continuous discovery and hypothesis-driven experimentation, rapidly developing prototypes to assess feasibility and potential impact.
    • Partner with business stakeholders to translate non-technical requirements into actionable AI/ML exploration paths.
  • RAG-Focused AI/ML Development:
    • Develop and prototype RAG-based architectures, including embedding pipelines, retrieval strategies, and transformer-based generative components.
    • Explore and validate new approaches for retrieval, indexing, and multimodal document understanding.
    • Apply validation, safety, and explainability practices in support of aerospace/defense requirements.
  • MPC & Real-Time Decisioning Exploration:
    • Design and prototype MPC-aligned models incorporating predictive modeling, optimization, and reinforcement-learning-based control.
    • Develop signal processing, perception, and planning pipelines supporting MPC control loops.
    • Use GPU acceleration, simulation environments, and HPC resources to support MPC experimentation.
  • Advanced AI/ML Modeling & Technical Leadership:
    • Architect, train, and optimize advanced models including transformers, GANs, RL agents, and real-time systems.
    • Provide technical leadership, mentor engineers, and guide cross-functional teams.
  • Safety, Validation & Integration Support:
    • Develop validation and testing frameworks ensuring compliance with safety and reliability standards.
    • Support integration teams with prototypes, documentation, and technical insights as required.

Qualifications You Must Have:

  • Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
  • 10+ years of experience in a related field.
  • Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 12 years of related experience is required.
  • Higher level relevant degree may substitute for experience.
  • Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic). Demonstrated ability to design and optimize generative AI models (e.g., transformers) and neural networks for complex applications.
  • Extensive experience architecting, deploying, and optimizing AI/ML systems, including ANNs, CNNs, and RNNs, in large-scale or mission-critical environments. Led efforts to improve model performance and reliability in production settings.
  • Strong proficiency in programming languages such as Python, C++, C# or Java, with experience in building scalable AI/ML systems.
  • Demonstrated experience leading teams or projects, including mentoring junior staff.
  • Proven track record of deploying AI/ML models in production environments and optimizing them for real-world use cases.
  • Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications.
  • Experience designing and optimizing generative AI models including transformers and GANs.
  • Experience building or integrating transformer-based models for retrieval-augmented or hybrid reasoning systems.
  • Proficiency designing embedding, retrieval, or indexing pipelines for large, multi-source datasets.
  • Familiarity with explainable AI (XAI) techniques for safety-critical environments.
  • Hands-on experience with reinforcement learning and real-time systems applicable to MPC.

Qualifications We Prefer:

  • Master's degree + additional years experience, or Ph.D. in Artificial Intelligence, Machine Learning, or a related field.
  • Experience with hardware acceleration technologies (e.g., CUDA, TensorRT) and high-performance computing systems.
  • Background in autonomous systems, robotics, or sensor fusion.
  • Familiarity with Agile/DevOps methodologies for software development.
  • Certifications in AI/ML or related fields, such as AWS Certified Machine Learning Specialty or Google Professional Machine Learning Engineer.
  • Deep understanding and practical application of Agile/DevOps in large-scale AI/ML projects.
  • Demonstrated experience with reinforcement learning and generative AI models in production or research settings.
  • Advanced proficiency in GPU programming, parallel/distributed computing, and optimizing ML workloads for performance.
  • Expertise in designing and implementing complex ML pipelines, including clustering, dimensionality reduction, generative modeling, and reinforcement learning, aligned to mission objectives and HMI systems.
  • Skilled in analyzing massive, multi-source datasets and delivering end-to-end autonomy software solutions, from requirements to deployment and maintenance.
  • Working knowledge of hardware acceleration technologies (CUDA, TensorRT), edge AI deployments, and explainable AI (XAI) methods.
  • Exposure to or interest in quantum computing for ML applications.

Essential Functions:


  • Contribute to AI/ML innovation and prototyping projects from exploration through technical feasibility assessment.
  • Support cross-functional engineering teams and integration efforts as needed.
  • Travel occasionally (10-20%) to customer sites, test facilities, or conferences.
  • Work in a hybrid office environment, balancing hands-on research with technical leadership.
  • Ensure compliance with safety, regulatory, and cybersecurity standards for AI/ML systems.

This posting will be open for application for a minimum of 5 days and may be extended based on business needs.

Estimated Starting Salary Range: $143,487.14 - $197,294.82. Compensation varies depending on a wide array of factors, such as candidates' key skills, relevant work experience, and education/training/certifications. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled.

SNC offers annual incentive pay based upon performance that is commensurate with the level of the position.

SNC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more.

IMPORTANT NOTICE:

This position requires the ability to obtain and maintain a Secret U.S. Security Clearance. U.S. Citizenship status is required as this position needs an active U.S. Security Clearance for employment. Non-U.S. citizens may not be eligible to obtain a security clearance. The Department of Defense Consolidated Adjudications Facility (DoD CAF), a federal government agency, handles the adjudicative aspects of the security clearance eligibility process for industry applicants. Adjudicative factors which affect the outcome of the eligibility determination include, but are not limited to, allegiance to the U.S., foreign influence, foreign preference, criminal conduct, security violations and illegal drug use.

Learn more about the background check process for Security Clearances.

SNC is a global leader in aerospace and national security committed to moving the American Dream forward. We're known and respected for our mission and execution focus, agility, and disruptive and rapid innovation. We provide leading edge technologies and transformative solutions that support our nation's most critical security needs. If you are mission-focused, thrive in collaborative environments, and want to make our country stronger with state-of-the-art technologies that safeguard freedom, join our team!

SNC is an Equal Opportunity Employer committed to an environment free of discrimination. Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran or other characteristics protected by law.


What Sierra Nevada Corporation employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom