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Neural Engineer Jobs in Colorado (NOW HIRING)

Pwc

AI Engineer

Denver, CO · On-site

$50K - $112K/yr

... AI Engineer, you will be at the forefront of transforming raw data into actionable insights ... neural networks and deep learning methods for advanced AI applications - Managing data quality and ...

Sierra Nevada Corporation

Sr AI/ML Engineer

Englewood, CO · On-site

$103K - $142K/yr

Demonstrated ability to design and optimise generative AI models (transformers) and neural networks ... Advanced proficiency in GPU programming, parallel/distributed computing, and optimizing ML ...

Pwc

AI Engineer

Denver, CO · On-site

$55K - $187K/yr

... neural network methodologies to optimize AI model performance - Managing data pipelines to validate efficient data flow and processing - Building and maintaining relationships with stakeholders to ...

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Neural Engineer information

See Colorado salary details

$62.6K

$117.4K

$213.5K

How much do neural engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for neural engineer in Colorado is $117,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,600.00 and $139,300.00 per year, depending on experience, location, and employer.

What does a neural engineer do?

A Neural Engineer applies principles from neuroscience, engineering, and computer science to develop technologies that interface with the nervous system. This includes designing brain-computer interfaces, neuroprosthetics, and medical devices for treating neurological disorders. They work with signal processing, machine learning, and biomedical hardware to understand and manipulate neural activity. Their work has applications in healthcare, rehabilitation, and human augmentation.

What are the key skills and qualifications needed to thrive as a neural engineer?

To thrive as a Neural Engineer, you need a strong background in biomedical engineering, neuroscience, and signal processing, often supported by an advanced degree in a related field. Proficiency with tools like MATLAB, Python, neural data acquisition systems, and familiarity with medical device regulations or certifications are commonly required. Problem-solving abilities, interdisciplinary teamwork, and effective communication set standout candidates apart. These skills and qualities are crucial for innovating and safely developing neural devices and technologies that bridge engineering and neuroscience.

What types of projects and collaborations can a neural engineer expect to be involved in?

As a Neural Engineer, you may work on projects ranging from designing brain-computer interfaces and neural prosthetics to analyzing complex neural signals for clinical or research applications. Collaboration with neuroscientists, clinicians, software developers, and hardware engineers is common, ensuring a multidisciplinary approach to solving neurological challenges. Your daily responsibilities might include data analysis, prototyping, testing devices, and presenting findings to your team. This role offers opportunities to influence cutting-edge research and directly contribute to advancements in healthcare and neurotechnology.

How much does a neural engineer make?

The average salary for a neural engineer typically ranges from $80,000 to $130,000 annually, depending on experience, education, and location. Professionals in this field often hold advanced degrees in neuroscience, engineering, or related areas and work in research institutions, healthcare, or tech companies specializing in brain-computer interfaces and neural technologies.

Is neural engineering a good career?

Neural engineering is a growing 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 career can be rewarding for those interested in innovative medical solutions and interdisciplinary work.

What jobs can you do with neural engineering?

Neural engineers can work in research and development roles focused on brain-computer interfaces, neural prosthetics, and neurotechnology devices. They often find employment in healthcare, biotech, and academic settings, applying skills in signal processing, neuroscience, and engineering design to develop innovative solutions for neurological disorders and cognitive enhancement.

What are popular job titles related to Neural Engineer jobs in Colorado?

For Neural Engineer jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Neural Engineer jobs in Colorado look for?

The top searched job categories for Neural Engineer jobs in Colorado are:

Neural Engineer jobs near you
Infographic showing various Neural Engineer job openings in Colorado as of September 2026, with employment types broken down into 1% Internship, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $117,383 per year, or $56.4 per hour.

Software Engineer I, Perception (New Grad)

Denver, CO • On-site

True Anomaly
Guided Missile and Space Vehicle Manufacturing • 11 - 50 employees
Learn more about True Anomalyexternal

Full-time

Posted 20 days ago

Job description

Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it.
OUR MISSION
True Anomaly delivers decisive capabilities for space superiority. We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors - enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground.
OUR VALUES
  • Be the offset. We create asymmetric advantages with creativity and ingenuity.
  • What would it take? We challenge assumptions to deliver ambitious results.
  • It's the people. Our team is our competitive advantage and we are better together.

YOUR MISSION
You'll work on hybrid perception systems combining classical computer vision with modern deep learning for autonomous spacecraft: building multi-object tracking pipelines that fuse neural network detections with Kalman filtering, developing coordinate transformation chains from pixels to orbital frames, training models on synthetic space imagery, and deploying algorithms onboard under strict compute/power constraints.
Your work enables spacecraft to detect objects against star fields, track multiple targets through occlusions, discriminate threats from decoys, and generate angle measurements for navigation - using both classical geometric methods and learned representations where each approach excels. This is entry-level work blending traditional robotics perception with modern ML. You'll implement Extended Kalman Filters, train neural networks in PyTorch, write C++ flight code, and see your algorithms operate in orbit.
This is a 3 month temporary employment engagement. There is potential to convert to regular employment based on performance and business need.
RESPONSIBILITIES
  • Implement classical tracking algorithms: Extended Kalman Filters for state estimation, Hungarian algorithm for data association, track management logic (tentative/confirmed/coasted tracks)
  • Train neural networks for detection and classification: YOLO for object detection, ResNet-based classifiers for threat discrimination, learned appearance features for re-identification
  • Build hybrid perception pipelines: neural network detections → classical tracking → coordinate transformations → angle-only measurements for navigation
  • Develop image processing chains: hot pixel filtering, adaptive thresholding, centroiding, connected component analysis, star catalog matching
  • Deploy models to edge hardware: quantize neural networks (INT8), integrate with C++ inference engines (ONNX Runtime, TensorRT), optimize for space-qualified processors
  • Implement coordinate transformations: pixel → camera frame → body frame → Earth-Centered Inertial (ECI), accounting for lens distortion and attitude uncertainty
  • Generate synthetic training data: render spacecraft in Blender with domain randomization (lighting, attitudes, backgrounds), create labeled datasets for rare scenarios
  • Validate end-to-end performance: software-in-the-loop simulation, processor-in-the-loop testing, hardware-in-the-loop with real camera feeds

QUALIFICATIONS
  • Currently pursuing or recently completed Bachelor's or Master's degree in computer science, electrical engineering, robotics, aerospace engineering, or related technical field
  • Coursework in both computer vision and estimation theory (or willingness to learn both)
  • Proficiency in Python; some exposure to C++ (we'll teach you more)
  • Familiarity with either classical tracking (Kalman filters, data association) OR deep learning (PyTorch, training neural networks)
  • Understanding of linear algebra, probability, and coordinate transformations
  • Ability to read research papers from both robotics (ICRA, IROS) and ML venues (CVPR, NeurIPS) and implement algorithms
  • Strong debugging skills: tracking down lost tracks, numerical instability, and model failure modes
  • Eagerness to learn the intersection of classical perception and modern ML
  • U.S. Citizen (required for facility access and government contracts)

PREFERRED SKILLS AND EXPERIENCE
  • Experience with Extended Kalman Filters, multi-object tracking, or state estimation
  • Familiarity with neural network training in PyTorch or TensorFlow: object detection (YOLO, Faster R-CNN), classification, or segmentation
  • Understanding of coordinate frames: camera intrinsics/extrinsics, quaternions, rotation matrices, ECI/LVLH/RIC frames
  • Exposure to model optimization for edge deployment: quantization (INT8, FP16), ONNX, TensorRT
  • Experience with OpenCV, image processing pipelines, or classical feature extraction
  • Coursework in optimal estimation, sensor fusion, or probabilistic robotics (Kalman/particle filters)
  • Prior work with synthetic data generation, Blender/Unreal for rendering, or domain randomization
  • Understanding of data association algorithms: Hungarian algorithm, auction algorithm, JPDA
  • Familiarity with tracking-by-detection pipelines: detection → association → update → track management
  • Experience debugging visual systems: false positives, missed detections, track ID switches, covariance tuning
  • Prior internship or project deploying algorithms to embedded systems (Jetson, mobile, ROS)
  • Exposure to multi-modal perception: fusing camera + IMU, camera + lidar, or learned sensor fusion

COMPENSATION
  • Base Salary:
    • Denver: $75,000
    • Long Beach: $80,000

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience.
ADDITIONAL REQUIREMENTS
  • Work Location-Successful candidates will be located near Centennial, CO or Long Beach, CA.
  • Work environment-the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.
  • Physical demands-the physical demands of the job, including bending, sitting, lifting and driving.

This position will be open until it is successfully filled. To submit your application, please follow the directions below.
#LI-Onsite
To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.
True Anomaly is committed to equal employment opportunity on any basis protected by applicable state and federal laws. If you have a disability or additional need that requires accommodation, please do not hesitate to let us.

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