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Artificial Intelligence Engineer Fpga Jobs (NOW HIRING)

Staffingine LLC

Artificial Intelligence Engineer

Bellevue, WA · On-site

$129K - $155K/yr

Job Title: Artificial Intelligence Engineer Job Location: Bellevue - Washington Job Type: Contract * Lead the development and deployment of machine learning models and analytical solutions for ...

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SCATR Corp.

Artificial Intelligence Engineer

Cleveland, OH

$111K - $133K/yr

We are looking to add an experienced Artificial Intelligence (AI) Engineer to our dynamic team and contribute to the development of a robust AI-enabled solution. As an AI Engineer, you will be ...

Epsilon

Artificial Intelligence Engineer

Irving, TX

$73K - $136K/yr

Overview How You'll Make an Impact As an AI Engineer, you will play a critical role in building and ... MS degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (or ...

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All JobsArtificial Intelligence Engineer Fpga Jobs

Artificial Intelligence Engineer Fpga information

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$85K

$147.3K

$198.5K

How much do artificial intelligence engineer fpga jobs pay per year?

As of Jul 4, 2026, the average yearly pay for artificial intelligence engineer fpga in the United States is $147,315.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,000.00 and $167,000.00 per year, depending on experience, location, and employer.

What is the difference between Artificial Intelligence Engineer Fpga vs Machine Learning Engineer?

AspectArtificial Intelligence Engineer FpgaMachine Learning Engineer
Required CredentialsBachelor's or Master's in Computer Engineering, Electrical Engineering, or related fields; FPGA design certificationsBachelor's or Master's in Computer Science, Data Science, or related fields; ML certifications
Work EnvironmentDesigning and implementing AI algorithms on FPGA hardware, often in embedded systems or hardware accelerationDeveloping, testing, and deploying ML models primarily in software environments
Industry UsageHardware-focused AI applications in telecommunications, automotive, and embedded systemsSoftware-focused AI applications in tech, finance, healthcare, and more

While both roles involve AI, the Artificial Intelligence Engineer Fpga specializes in hardware acceleration using FPGA chips, whereas the Machine Learning Engineer focuses on developing ML models primarily in software. The FPGA role requires hardware design skills, while the ML engineer emphasizes software development and data analysis.

What are some common challenges faced when deploying AI models on FPGA platforms as an Artificial Intelligence Engineer?

One of the main challenges in this role is optimizing AI models to fit within the limited resources and parallel architecture of FPGAs, which often requires extensive knowledge of both hardware and software design. Additionally, ensuring low latency and high throughput while maintaining model accuracy can be complex, especially when working with large or sophisticated neural networks. Collaboration with hardware engineers and data scientists is also essential to balance performance trade-offs and efficiently translate algorithms into deployable FPGA solutions.

What are Artificial Intelligence Engineer FPGA roles?

Artificial Intelligence Engineer FPGA roles involve designing, implementing, and optimizing AI algorithms to run efficiently on Field Programmable Gate Arrays (FPGAs). These engineers bridge the gap between hardware and software by developing custom hardware accelerators for AI tasks such as machine learning inference and computer vision. Their responsibilities often include hardware description language (HDL) programming, optimizing data pipelines, and collaborating with AI researchers to translate models into hardware implementations. This role is essential in industries where high-speed processing with low power consumption is critical, such as autonomous vehicles, robotics, and telecommunications.

What are the key skills and qualifications needed to thrive as an Artificial Intelligence Engineer specializing in FPGA, and why are they important?

To excel as an Artificial Intelligence Engineer specializing in FPGA, you need a solid background in computer engineering, digital design, and AI/ML algorithms, often with a degree in electrical engineering or computer science. Proficiency in FPGA development tools (such as Xilinx Vivado or Intel Quartus), HDL languages (VHDL/Verilog), and frameworks like TensorFlow or PyTorch is essential. Strong problem-solving skills, attention to detail, and effective teamwork are vital soft skills for this role. Mastery of these skills ensures efficient deployment of AI models on hardware, high-performance solutions, and successful collaboration across multidisciplinary teams.
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Artificial Intelligence Engineer Fpga jobs near you
Infographic showing various Artificial Intelligence Engineer Fpga job openings in the United States as of June 2026, with employment types broken down into 17% Internship, 66% Full Time, and 17% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $147,315 per year, or $70.8 per hour.

Artificial Intelligence Engineer

Darksaber Labs

Alexandria, VA • On-site

$120K - $200K/yr

Full-time

Posted 5 days ago

Job description

About Darksaber Labs
Darksaber Labs is a new Electronic Warfare (EW) start up founded by EW Operators.
About the role
  • The Artificial Intelligence Engineer role is intended to aid in product design and implementation.

What you'll do
  • Design and implement traditional machine learning and generative artificial intelligence capabilities.
  • Conduct research and development of current and leading edge trends.
  • Ensure quality assurance and ability to move capabilities into production.

Qualifications
  • Clearance
  • Programming
  • Education or equivalent work experience in ML/AI
  • Prior IC/DoW experience is a plus

Salary range is $120,000 - $200,000 a year.

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