ZipRecruiter

Log In

1

Embedded Ai Engineer Jobs (NOW HIRING)

MatchPoint Solutions

Embedded AI Engineer

Sunnyvale, CA · On-site

$156K - $206K/yr

Embedded AI Engineer Location: Sunnyvale, CA Employment Type: 6+ Month Extendable Contract Pay Range: USD 70-80/HR - Role Overview/Job Responsibilities About this opportunity - Embedded AI Engineer ...

Honeywell

Director Embedded AI Engineering

Atlanta, GA · On-site

We are seeking someone with embedded AI experience, particularly with GPUs or AI accelerators, and ... Advanced degree in Computer Science, Electrical Engineering, or related technical field preferred.

Honeywell

Director Embedded AI Engineering

Atlanta, GA · On-site

$126K - $166K/yr

We are seeking someone with embedded AI experience, particularly with GPUs or AI accelerators, and ... Advanced degree in Computer Science, Electrical Engineering, or related technical field preferred.

Terex

AI Engineer III

Austin, TX · On-site

$57 - $76.50/hr

AI Engineer III Operating Company : Environmental Solutions Group Location: Austin, TX Reports to ... Lead development and deployment of AI models on embedded and edge devices, ensuring performance ...

Terex Corporation

AI Engineer III

Austin, TX · On-site

$57 - $76.50/hr

AI Engineer III Operating Company : Environmental Solutions Group Location: Austin, TX Reports to ... Lead development and deployment of AI models on embedded and edge devices, ensuring performance ...

next page

Showing results 1-20

All JobsEmbedded Ai Engineer Jobs

Embedded Ai Engineer information

See salary details

$70K

$153.4K

$174K

How much do embedded ai engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for embedded ai engineer in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is an Embedded AI Engineer?

An Embedded AI Engineer is a professional who designs, develops, and implements artificial intelligence (AI) algorithms and models directly onto embedded systems, such as microcontrollers or edge devices. Their work involves optimizing AI solutions to run efficiently on hardware with limited computing resources, power, and memory. They collaborate with hardware engineers and software developers to integrate machine learning, computer vision, or other AI functionalities into products like smart appliances, autonomous vehicles, or IoT devices. Their expertise helps bring intelligent features directly to devices, enabling real-time decision-making without needing constant cloud connectivity.

What is the difference between Embedded Ai Engineer vs Machine Learning Engineer?

CriteriaEmbedded Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related; knowledge of embedded systemsBachelor's or Master's in Computer Science, Data Science, or related; strong programming skills
Work EnvironmentEmbedded systems, IoT devices, hardware integrationData centers, cloud platforms, software development environments
Employer & Industry UsageConsumer electronics, automotive, IoT companiesTech firms, startups, research institutions
Common Search & ComparisonYesNo

Embedded Ai Engineers focus on integrating AI algorithms into embedded hardware and IoT devices, requiring knowledge of hardware constraints and embedded programming. Machine Learning Engineers develop models primarily for software applications and data analysis. While both roles involve AI, Embedded Ai Engineers specialize in hardware-software integration within embedded systems, whereas Machine Learning Engineers work on developing and deploying AI models in software environments.

What are the key skills and qualifications needed to thrive as an Embedded AI Engineer, and why are they important?

To thrive as an Embedded AI Engineer, you need expertise in embedded systems, AI/ML algorithms, programming languages like C/C++ and Python, and typically a degree in computer engineering or a related field. Familiarity with development tools such as TensorFlow Lite, ONNX, embedded Linux, and microcontroller platforms is essential, along with experience deploying AI models on resource-constrained devices. Strong problem-solving, collaboration, and communication skills help you work effectively in multidisciplinary teams and address real-world challenges. These skills ensure efficient integration of AI into embedded systems, enabling innovative, high-performance solutions for edge computing.

How does an Embedded AI Engineer typically collaborate with hardware and software teams during a project?

Embedded AI Engineers work closely with both hardware and software teams to ensure AI models are efficiently integrated into resource-constrained devices. They often collaborate with hardware engineers to optimize model performance based on device limitations like memory and processing power. At the same time, they coordinate with software developers to design efficient firmware and manage data pipelines. Regular cross-functional meetings and code reviews are common to address integration challenges and maintain alignment throughout the project lifecycle.
More about Embedded Ai Engineer jobs
What cities are hiring for Embedded Ai Engineer jobs? Cities with the most Embedded Ai Engineer job openings:
What states have the most Embedded Ai Engineer jobs? States with the most job openings for Embedded Ai Engineer jobs include:
What job categories do people searching Embedded Ai Engineer jobs look for? The top searched job categories for Embedded Ai Engineer jobs are:
Embedded Ai Engineer jobs near you
Infographic showing various Embedded Ai Engineer job openings in the United States as of May 2026, with employment types broken down into 95% Full Time, 1% Part Time, and 4% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
Embedded AI Engineer

Embedded AI Engineer

MatchPoint Solutions

Sunnyvale, CA • On-site

$156K - $206K/yr

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

MatchPoint Solutions is a fast-growing, young, energetic global IT-Engineering services company with clients across the US. We provide technology solutions to various clients like Uber, Robinhood, Netflix, Airbnb, Google, Sephora, and more! More recently, we have expanded to working internationally in Canada, China, Ireland, UK, Brazil, and India. Through our culture of innovation, we inspire, build, and deliver business results, from idea to outcome. We keep our clients on the cutting edge of the latest technologies and provide solutions by using industry-specific best practices and expertise.
We are excited to be continuously expanding our team. If you are interested in this position, please send over your updated resume. We look forward to hearing from you!
Job Title: Embedded AI Engineer
Location: Sunnyvale, CA
Employment Type: 6+ Month Extendable Contract
Pay Range: USD 70-80/HR
- Role Overview/Job Responsibilities
About this opportunity - Embedded AI Engineer We are seeking an experienced Embedded AI Engineer to join our team in validating PyTorch-based Large Language Models (LLMs) using CUDA SDK APIs. The successful candidate will be responsible for debugging, extending, and replacing the underlying CUDA code to ensure seamless functionality on our company-specific AI processors.
Key Responsibilities:
• Validate PyTorch-based LLMs on company-specific AI processors using CUDA SDK APIs
• Debug and troubleshoot issues related to CUDA code integration with PyTorch models
• Extend and modify CUDA code to optimize performance on company-specific AI processors
• Replace existing CUDA code with custom implementations to meet specific requirements
• Collaborate with cross-functional teams to ensure successful integration of LLMs with company-specific AI processors
• Develop and maintain validation frameworks and tools for PyTorch-based LLMs
• Analyze and optimize the performance of LLMs on company-specific AI processors Requirements
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related fields
• Strong experience with CUDA programming and PyTorch framework
• In-depth knowledge of deep learning models, particularly Large Language Models (LLMs)
• Proficiency in C++ and Python programming languages
• Experience with debugging and troubleshooting complex software issues
• Excellent problem-solving skills and attention to detail
• Strong communication and collaboration skills
Nice to Have:
• Experience with AI processor architecture and design
• Knowledge of other deep learning frameworks, such as TensorFlow
MatchPoint Solutions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Apply