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Mid Level Neuromorphic Computing Jobs in Albuquerque, NM

I Pulse Group

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Computational Physicist (Early, Mid-Career, or Senior Level)

Albuquerque, NM · On-site

$95K - $250K/yr

Computational Physicist (Early, Mid-Career, or Senior Level) I-Pulse Albuquerque LLC We are seeking ... Managing computing systems and diverse operating systems (Linux, macOS, Windows) or small clusters.

Hp

Inside Account Executive

Rio Rancho, NM · Remote

$53K - $160K/yr

To lead meetings with high variety of senior-level stakeholders * To leverage customer, industry ... computing, software, services and IT infrastructure to serve more than 1 billion customers in over ...

All JobsMid Level Neuromorphic Computing JobsMid Level Neuromorphic Computing Jobs in Albuquerque, NM

Mid Level Neuromorphic Computing information

See Albuquerque, NM salary details

$10.7K

$84K

$109.5K

How much do mid level neuromorphic computing jobs pay per year?

As of Aug 22, 2026, the average yearly pay for mid level neuromorphic computing in Albuquerque, NM is $84,008.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,200.00 and $104,200.00 per year, depending on experience, location, and employer.

What is a mid level neuromorphic computing professional?

Mid level neuromorphic computing professionals are specialists with several years of experience who design, develop, and optimize hardware and software systems inspired by the structure and function of the human brain. They typically work on building and programming neuromorphic chips, developing algorithms that mimic neural processes, and integrating these systems into real-world applications such as robotics or edge computing. Their expertise bridges neuroscience, computer engineering, and artificial intelligence, and they often collaborate with interdisciplinary teams to advance brain-inspired computing technologies.

What are the key skills and qualifications needed to thrive as a mid level neuromorphic computing engineer?

To thrive as a Mid Level Neuromorphic Computing Engineer, you need a solid background in computer engineering, neuroscience, and machine learning, usually supported by a relevant degree and experience with neural network architectures. Familiarity with tools like Python, MATLAB, TensorFlow, and simulation platforms such as NEST or SpiNNaker, along with knowledge of specialized hardware, is typically required. Strong problem-solving, collaboration, and communication skills help you innovate and effectively share complex ideas with multidisciplinary teams. These skills and qualifications are crucial for developing advanced neuromorphic systems that bridge neuroscience and AI, pushing the boundaries of efficient computing.

What are some common challenges faced by professionals in mid level neuromorphic computing roles, and how can they be addressed?

Professionals in mid-level neuromorphic computing roles often encounter challenges such as integrating novel hardware with existing software systems, managing the complexity of neural-inspired algorithms, and keeping pace with rapid advancements in the field. Collaborating closely with multidisciplinary teams—including hardware engineers, data scientists, and neuroscientists—can help address these challenges. Additionally, staying updated on the latest research and industry trends, as well as participating in collaborative projects, can enhance problem-solving skills and foster innovation in this evolving area.

What is the difference between Mid Level Neuromorphic Computing vs Mid Level Machine Learning Engineer?

AspectMid Level Neuromorphic ComputingMid Level Machine Learning Engineer
Required CredentialsBachelor's in Computer Science, Electrical Engineering, or related field; knowledge of neuromorphic hardwareBachelor's in Computer Science, Data Science, or related; experience with ML frameworks
Work EnvironmentResearch labs, hardware development, AI hardware companiesTech companies, startups, data-driven organizations
Industry UsageAI hardware, neuromorphic chip design, cognitive computingSoftware development, AI applications, data analysis

Mid Level Neuromorphic Computing professionals focus on hardware and cognitive architectures inspired by the brain, often working with specialized hardware and research teams. In contrast, Mid Level Machine Learning Engineers develop algorithms and models primarily in software to solve data-driven problems. Both roles require a strong technical background but differ in their focus on hardware versus software applications.

What are popular job titles related to Mid Level Neuromorphic Computing jobs in Albuquerque, NM?

For Mid Level Neuromorphic Computing jobs in Albuquerque, NM, the most frequently searched job titles are:

What job categories do people searching Mid Level Neuromorphic Computing jobs in Albuquerque, NM look for?

The top searched job categories for Mid Level Neuromorphic Computing jobs in Albuquerque, NM are:

Mid Level Neuromorphic Computing jobs near you
Infographic showing various Mid Level Neuromorphic Computing job openings in Albuquerque, NM as of July 2026, with employment types broken down into 70% Full Time, 20% Part Time, 1% Temporary, and 9% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $84,008 per year, or $40.4 per hour.

Senior Electronics / Computer Hardware Engineer - Autonomous Systems

Red Gate Group

Albuquerque, NM • On-site

$107K - $143K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 22 days ago

Job description

Description
We are seeking a Senior Electronics or Computer Hardware Engineer specializing in Autonomous Systems to directly support the Defense Threat Reduction Agency (DTRA). This is a full-time, on-site position located at Kirtland Air Force Base (AFB) in Albuquerque, NM.
In this role, you will serve as the principal technical authority responsible for designing, modifying, and evaluating autonomous hardware systems, unmanned aerial/ground vehicles (UxS), and robotic edge-computing nodes deployed into GPS-denied, communication-constrained, and hazardous environments. Your expertise will bridge the gap between autonomous physical hardware, edge-processing, and multi-domain sensing architectures-ensuring these systems can navigate, map, and assess complex Underground Facilities (UGFs) and hardened deeply buried targets (HDBTs).
Key Responsibilities
  • Autonomous Hardware Design: Lead the electrical architecture design, component selection, and ruggedization of embedded computing platforms, sensors, and power distribution systems for autonomous systems deployed in subterranean environments.
  • Subterranean Sensing & Payload Integration: Design and integrate specialized sensor payloads (e.g., radiation detectors, gas sensors, LiDAR, multi-spectral cameras) onto autonomous platforms to map internal UGF geometries and detect threat signatures.
  • M&S and Hazard Tool Interface: Ensure physical sensor hardware outputs and autonomous telemetry streams are formatted to feed directly into DoD predictive toolsets, providing real-time bounding and source-term data for HPAC and VLSTRACK environmental dispersion models.
  • Embedded Edge-Computing: Optimize edge-processing architectures (FPGA, GPU, microcontrollers) to handle simultaneous localization and mapping (SLAM), autonomous navigation algorithms, and localized data fusion without relying on external communication loops.
  • Hardware-in-the-Loop (HIL) Testing: Develop and execute rigorous HIL testing frameworks to validate autonomous hardware performance against simulated underground environments, electromagnetic interference (EMI), and extreme physical degradation.
  • Field Test Integration: Collaborate with Kirtland-based Test & Evaluation (T&E) teams to physically field-test robotic and autonomous hardware configurations in specialized underground test beds and regional ranges.
  • Technical Leadership: Mentor junior to mid-level electronics engineers, hardware designers, and roboticists at Kirtland AFB, establishing rigorous engineering, testing, and hardware safety baselines.
  • Interagency Collaboration: Present complex hardware architectures, autonomous systems capabilities, and vulnerability testing results to executive DTRA leadership, combatant commands (COCOMs), and international defense partners.

Required Qualifications
  • Education: Bachelor's degree in Electrical Engineering, Computer Engineering, Robotics Engineering, or a highly relevant STEM discipline; Master's degree or Doctorate (Ph.D.) preferred.
  • Experience: Minimum of 10+ years of progressive engineering experience, with a heavy emphasis on embedded electronics design, computer hardware architectures, and autonomous/robotic systems within the Department of Defense (DoD) or intelligence community space.
  • Specialized Domain Expertise: Comprehensive expertise in circuit design (PCB layout, signal integrity), embedded architectures (ARM, FPGAs, microcontrollers), and autonomous system platforms (UAV, UGV, UxS) optimized for complex or Underground Facilities (UGFs).
  • Predictive Tool Familiarity: Strong working knowledge of how hardware sensor arrays and autonomous data acquisition pipelines interface with and constrain DoD hazard prediction toolsets, specifically Hazard Prediction and Assessment Capability (HPAC) and Vapor, Liquid, and Solid Tracking (VLSTRACK).
  • Security Clearance: An active U.S. Government Top Secret / Sensitive Compartmented Information (TS/SCI) security clearance
  • Technical Stack: Advanced proficiency with electrical CAD tools (e.g., Altium Designer, Cadence Allegro), hardware description languages (VHDL/Verilog), and low-level programming (C/C++, Python) for embedded systems and ROS (Robot Operating System).

Preferred Experience
  • GPS-Denied Navigation: Hands-on experience developing or testing hardware architectures that utilize visual-inertial odometry, ultra-wideband (UWB) tracking, or non-traditional navigation in GPS-denied environments.
  • Radiation Hardening & Ruggedization: Familiarity with MIL-STD-810 (environmental engineering) and MIL-STD-461 (electromagnetic compatibility) testing standards for electronics operating in extreme environments.
Company Description
The Red Gate Group, founded in 2006, is a Service-Disabled Veteran-Owned Company based in Chantilly, VA. As an SDVOSB, the Red Gate Group has established a reputation for delivering quality multi-tiered services in intelligence analysis, strategic planning, program management, policy development, operational design, and technology integration. RGG delivers high-quality, customer-centric solutions around the world-from the foxhole to the highest levels of Government. Our motto, "Making a Difference for Country and Client," reflects our deep commitment to national security and service excellence. As an employer of choice, we offer comprehensive benefits including flexible time off, 11 paid holidays, immediate 401(k) eligibility with a generous match, and full medical, dental, and vision coverage. Our employees enjoy 100% company-paid life insurance and disability benefits, along with professional development assistance for degrees and certifications. We foster a culture of growth and work-life balance, backed by our commitment to supporting both our clients' missions and our employees' success. Join our team and be part of an organization that values both service excellence and employee wellbeing.

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