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Embedded Engineer Jobs in Logan, UT (NOW HIRING)

AI Embedded Engineer IV

Logan, UT

$113K - $149K/yr

As an AI Embedded Engineer IV , you own the layer where artificial intelligence (AI) meets the machine. Models that run fine on a workstation have to run on an NVIDIA Jetson bolted to a vehicle ...

AI Embedded Engineer IV

Logan, UT · On-site

$113K - $149K/yr

As an AI Embedded Engineer IV, you own the layer where artificial intelligence (AI) meets the machine. Models that run fine on a workstation have to run on an NVIDIA Jetson bolted to a vehicle ...

AI Embedded Engineer IV

Logan, UT · On-site

$145K - $169K/yr

As an AI Embedded Engineer IV , you own the layer where artificial intelligence (AI) meets the machine. Models that run fine on a workstation have to run on an NVIDIA Jetson bolted to a vehicle ...

Perception Engineer IV

Mendon, UT · On-site

$100 - $130/hr

Integrate perception software with ASI's autonomous vehicle platforms, embedded computing systems ... Partner with systems engineers to define interfaces, requirements, failure responses, and ...

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Embedded Engineer information

See Logan, UT salary details

$60.3K

$132.1K

$149.9K

How much do embedded engineer jobs pay per year?

As of Aug 29, 2026, the average yearly pay for embedded engineer in Logan, UT is $132,128.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,300.00 and $149,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an embedded engineer?

To thrive as an Embedded Engineer, you need a solid background in computer science or electrical engineering, with strong skills in C/C++, microcontroller programming, and embedded systems design. Familiarity with real-time operating systems (RTOS), hardware debugging tools, and version control systems like Git is typically required, and certifications such as Certified Embedded Systems Engineer (CESE) can be beneficial. Strong problem-solving abilities, attention to detail, and effective communication are standout soft skills in this field. These competencies are crucial for developing reliable, efficient embedded solutions that integrate seamlessly with hardware and meet user requirements.

What are some common challenges faced by embedded engineers when working on cross-functional teams?

Embedded Engineers often collaborate closely with hardware designers, software developers, and test engineers, which can present challenges related to communication and integration. Aligning the firmware with hardware specifications, managing resource constraints, and ensuring timely debugging across different platforms are frequent hurdles. To succeed, Embedded Engineers need strong communication skills and a collaborative mindset to bridge gaps between disciplines and deliver cohesive, reliable systems.

What is the difference between Embedded Engineer vs Firmware Engineer?

AspectEmbedded EngineerFirmware Engineer
Required CredentialsBachelor's in Electrical, Computer Engineering, or related fields; certifications like ARM or IoT certifications are commonBachelor's in Computer Engineering, Electrical Engineering, or related; often similar certifications in embedded systems or firmware development
Work EnvironmentDesigning and developing hardware-software integrated systems, often in industrial, automotive, or consumer electronicsWriting, testing, and debugging low-level code that runs directly on hardware devices like microcontrollers or embedded processors
Employer & Industry UsageElectronics manufacturers, automotive, aerospace, IoT companiesConsumer electronics, IoT devices, medical devices, automotive systems

Embedded Engineers and Firmware Engineers often work closely, but Embedded Engineers focus on both hardware and software integration, while Firmware Engineers specialize in low-level code development that runs directly on hardware. Both roles require similar skills and certifications, but their primary focus and work environment differ slightly.

Are embedded engineers in demand?

Embedded engineers are in high demand due to the growth of IoT devices, automotive systems, and consumer electronics. Skills in C/C++, real-time operating systems, and hardware integration are particularly valuable in this field, which offers strong job stability and opportunities across various industries.

What does an embedded engineer do?

An embedded engineer designs, develops, and tests software and hardware for embedded systems, which are specialized computing devices within larger machines or products. They work with microcontrollers, real-time operating systems, and programming languages like C or C++, often collaborating with hardware teams to ensure system functionality and reliability.

What are popular job titles related to Embedded Engineer jobs in Logan, UT?

For Embedded Engineer jobs in Logan, UT, the most frequently searched job titles are:

What job categories do people searching Embedded Engineer jobs in Logan, UT look for?

The top searched job categories for Embedded Engineer jobs in Logan, UT are:

Infographic showing various Embedded Engineer job openings in Logan, UT as of August 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $132,308 per year, or $63.6 per hour.

AI Embedded Engineer IV

Logan, UT

Autonomous Solutions
Industrial Machinery Manufacturing • 51 - 200 employees

$113K - $149K/yr

Full-time

Re-posted 12 days ago


Job description

At ASI, we are revolutionizing industries with state-of-the-art autonomous robotics solutions. Within the fields of agriculture, construction, landscaping, and logistics, we deliver technologies that enhance safety, productivity, and efficiency. With our core values of Simplicity, Safety, Transparency, Humility, Attention to Detail, Autonomy and Growth guiding everything we do, we're shaping the future of automation in dynamic markets.

As an AI Embedded Engineer IV, you own the layer where artificial intelligence (AI) meets the machine. Models that run fine on a workstation have to run on an NVIDIA Jetson bolted to a vehicle, reading Light Detection and Ranging (LiDAR) returns and depth camera frames, sharing compute and bandwidth with everything else on the platform, in dust and heat and vibration. Making that work is the job. You take trained models, get them running in real time on vehicle compute, retune them when field performance drifts, and build the software that moves data between sensors, compute, and the robot itself.

The role is deliberately split between software and hardware. Most of your week is embedded software: Robot Operating System (ROS) nodes on the vehicle, Python and C++ bridges between compute and robot control, runtime optimization, and debugging timing and synchronization problems across process and hardware boundaries. The rest is hands-on hardware. You will select and bring up sensors and compute, build the rigs that carry them, run the wiring and power, and fix electrical problems yourself rather than filing a ticket. As a Level IV engineer within ASI's five-level engineering structure, you independently lead complex initiatives, influence the team's technical direction, and provide technical guidance to other engineers, with broader platform strategy remaining aligned with engineering leadership and Level V technical authorities.

Responsibilities

  • Deploy trained models to embedded Central Processing Units (CPUs) and Graphics Processing Units (GPUs) on vehicle compute, owning export, optimization, quantization, and latency budgets.

  • Retrain and fine-tune existing models when field performance drifts, and validate the result on the vehicle rather than only on a benchmark.

  • Build and maintain ROS nodes, topics, and interfaces running on the vehicle, and keep them stable under real workloads.

  • Write the Python and C++ bridges that connect compute to robot control, sensor drivers, and the rest of the autonomy stack.

  • Profile and tune runtime performance against real constraints, including compute headroom, memory, thermal limits, and power budgets.

  • Bring up new sensors and compute hardware, including NVIDIA Jetson platforms, LiDAR units, and depth and vision systems, through provisioning, configuration, and calibration.

  • Design and build sensor and data-collection rigs, covering sensor selection, mounting, wiring, power, networking, and onboard recording, then take them into the field.

  • Debug hard cross-boundary problems spanning timing, synchronization, coordinate frames, machine motion, and compute limits.

  • Fabricate and modify the mounts, brackets, and fixtures your hardware needs, and build and debug supporting wiring, harnesses, and small custom circuits.

  • Characterize what you deliver honestly, including where it works, where it fails, and what conditions break it, so downstream teams know what they are inheriting.

  • Document approaches, assumptions, results, and known limitations, and hand off work the production teams can build on with confidence.

  • Provide technical guidance to other engineers on embedded deployment, sensor integration, and on-vehicle debugging.

Required Qualifications

  • Bachelor's degree in Robotics, Computer Science, Computer Engineering, Electrical Engineering, Mechanical Engineering, or a related technical field.

  • Substantial experience developing embedded, robotics, or autonomous system software. Graduate-level research experience in a relevant field counts toward this experience.

  • Demonstrated experience independently taking complex embedded or AI integration work from concept to a working, evaluated system on real hardware.

  • Advanced proficiency in C++ and Python.

  • Experience deploying trained neural networks to embedded or production runtime environments, including model export and runtime optimization.

  • Experience retraining or fine-tuning existing models and validating performance changes.

  • Strong experience with Robot Operating System (ROS or ROS 2) or comparable robotics middleware on real vehicles or robots.

  • Hands-on experience bringing up embedded compute platforms such as NVIDIA Jetson, including provisioning, drivers, and configuration.

  • Experience integrating LiDAR, depth cameras, or other vision systems, including calibration and data synchronization.

  • Working understanding of coordinate systems, geometric transformations, camera models, and sensor timing.

  • Experience with Linux, version control, automated testing, and containerized development.

  • Genuine willingness to work hands-on with hardware, including wiring sensors, assembling rigs, and debugging electrical and mechanical problems directly.

  • Strong analytical and debugging skills, and experience explaining results and limitations clearly while providing technical guidance to other engineers.

  • Willingness to travel to test sites as required.

Preferred Qualifications

  • Master's degree or Doctor of Philosophy (Ph.D.) in Robotics, Computer Science, Electrical Engineering, Computer Engineering, or a related discipline.

  • Experience with embedded AI or autonomy software on heavy equipment, agricultural machinery, construction vehicles, or mobile robots.

  • Experience with CUDA, TensorRT, or comparable GPU acceleration and inference optimization tooling.

  • Experience with PyTorch, TensorFlow, or comparable frameworks for fine-tuning existing models.

  • Experience with real-time constraints, deterministic scheduling, or time synchronization across distributed sensors.

  • Experience with Controller Area Network (CAN) based vehicle communication or other embedded bus protocols.

  • Experience with Computer-Aided Design (CAD), 3D printing, shop fabrication, microcontrollers, printed circuit board (PCB) design, or data acquisition systems.

  • Familiarity with state estimation, Kalman filtering, or probabilistic robotics.

  • Experience running experiments outdoors in off-road, low-light, dusty, or weather-exposed conditions.

Physical Requirements

  • Ability to remain in a stationary position at a computer workstation for extended periods.

  • Ability to operate a computer and other office productivity equipment continuously.

  • Ability to communicate and exchange information in person, via phone, and through electronic means.

  • Ability to traverse office, lab, shop, and field environments as required.

At Autonomous Solutions, Inc. (ASI), we are committed to fostering a diverse, inclusive, and equitable workplace where all employees and applicants have equal opportunities. We prohibit discrimination and harassment of any kind based on race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other legally protected characteristic. ASI complies with all applicable federal, state, and local laws regarding non-discrimination in employment and is dedicated to providing reasonable accommodations for individuals with disabilities throughout the hiring process.