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Fpga Deep Learning Jobs in Seattle, WA (NOW HIRING)

Senior FPGA Engineer

Seattle, WA · On-site

$120K - $225K/yr

... deep space. The rise of heavy-lift launch vehicles is shifting the industry from an era of mass ... For now, this does not include front-end, artificial intelligence, or machine learning development.

Senior FPGA Engineer

Seattle, WA · On-site

$120K - $225K/yr

... deep space. The rise of heavy-lift launch vehicles is shifting the industry from an era of mass ... For now, this does not include front-end, artificial intelligence, or machine learning development.

Senior FPGA Engineer

Seattle, WA · On-site

$120 - $225/hr

... deep space. The rise of heavy-lift launch vehicles is shifting the industry from an era of mass ... For now, this does not include front-end, artificial intelligence, or machine learning development.

Fpga Deep Learning information

See Seattle, WA salary details

$79.7K

$167.4K

$239.6K

How much do fpga deep learning jobs pay per year?

As of Aug 14, 2026, the average yearly pay for fpga deep learning in Seattle, WA is $167,354.00, according to ZipRecruiter salary data. Most workers in this role earn between $140,000.00 and $192,900.00 per year, depending on experience, location, and employer.

What is an FPGA Deep Learning engineer?

FPGA Deep Learning engineers are professionals who design, implement, and optimize deep learning models to run efficiently on Field-Programmable Gate Arrays (FPGAs). FPGAs are specialized hardware chips that can be programmed to perform specific computational tasks at high speeds and low power consumption. These engineers bridge the gap between artificial intelligence algorithms and hardware, ensuring that neural networks and AI applications can leverage FPGA advantages such as parallelism and flexibility. Their work is crucial in industries requiring real-time data processing, like autonomous vehicles, robotics, and edge computing.

What is the difference between Fpga Deep Learning vs Machine Learning Engineer?

AspectFpga Deep LearningMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, EE, or related; knowledge of FPGA programming and deep learning frameworksBachelor's or higher in CS, Data Science, or related; expertise in ML algorithms and software development
Work EnvironmentHardware-focused, embedded systems, FPGA development labsSoftware-focused, data centers, cloud platforms, or research labs
Industry UsageEmbedded AI, edge computing, specialized hardware accelerationData analysis, predictive modeling, software solutions across industries

While both roles involve AI and machine learning, Fpga Deep Learning specialists focus on hardware acceleration using FPGAs to optimize deep learning models, whereas Machine Learning Engineers develop and deploy ML algorithms primarily in software environments. The roles often overlap in AI projects but differ in technical focus and work environment.

What are the key skills and qualifications needed to thrive as an FPGA Deep Learning engineer?

To thrive as an FPGA Deep Learning Engineer, you need a solid background in digital design, hardware description languages (such as VHDL or Verilog), deep learning frameworks, and a relevant degree in electrical engineering, computer engineering, or a similar field. Familiarity with FPGA development tools (like Xilinx Vivado or Intel Quartus), hardware accelerators, and experience with deploying neural networks on embedded systems are typically required. Problem-solving ability, attention to detail, and strong collaboration skills are key soft skills that make a candidate stand out. These skills and qualities are essential for efficiently bridging the gap between AI algorithms and hardware implementations, ensuring high-performance, reliable solutions.

How do professionals in FPGA Deep Learning roles typically collaborate with software and data science teams?

FPGA Deep Learning professionals often work closely with software engineers and data scientists to optimize deep learning models for hardware acceleration. This collaboration involves translating neural network architectures from high-level frameworks (like TensorFlow or PyTorch) into efficient hardware implementations, communicating constraints or opportunities for parallelization, and iteratively refining models for performance. Regular meetings and code reviews are common to ensure alignment between hardware and software development. Effective communication and understanding of both domains are essential for successfully deploying deep learning solutions on FPGA platforms.

What are popular job titles related to Fpga Deep Learning jobs in Seattle, WA?

For Fpga Deep Learning jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Fpga Deep Learning jobs in Seattle, WA look for?

The top searched job categories for Fpga Deep Learning jobs in Seattle, WA are:

Infographic showing various Fpga Deep Learning job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $167,354 per year, or $80.5 per hour.

Senior FPGA Engineer

K2 Space

Seattle, WA • On-site

$120K - $225K/yr

Full-time

Re-posted 12 days ago


Job description

K2 is building the largest and highest-power satellites ever flown, unlocking performance levels previously out of reach across every orbit. Backed by $450M from leading investors including Altimeter Capital, Redpoint Ventures, T. Rowe Price, Lightspeed Venture Partners, Alpine Space Ventures, and others – with an additional $500M in signed contracts across commercial and US government customers – we're mass-producing the highest-power satellite platforms ever built for missions from LEO to deep space.

The rise of heavy-lift launch vehicles is shifting the industry from an era of mass constraint to one of mass abundance, and we believe this new era demands a fundamentally different class of spacecraft. Engineered to survive the harshest radiation environments and to fully capitalize on today's and tomorrow's massive rockets, K2 satellites deliver unmatched capability at constellation scale and across multiple orbits.

With multiple launches planned through 2026 and 2027, we're Building Bigger to develop the solar system and become a Kardashev Type II (K2) civilization. If you are a motivated individual who thrives in a fast-paced environment and you're excited about contributing to the success of a groundbreaking Series C space startup, we'd love for you to apply.

The Role

The software team at K2 strives to blur the lines between the various types of software development and encourages team members to get into parts of the stack they may not otherwise have experience with. This spectrum includes HDL programming (VHDL, SystemVerilog), embedded software on microcontrollers (Rust, C++), operating systems (Rust, C++, C), application software on flight computers (Rust, C++), GNC algorithms (Rust, C++), to test systems (Python), and many things inbetween. By doing this, we create a stronger team with more capable engineers. For now, this does not include front-end, artificial intelligence, or machine learning development.

As a part of the team, you will be responsible for the development and verification of FPGA firmware used to fly some of the largest spacecraft that have ever been flown. You will be able to write mission-critical code that controls propulsion systems, attitude control systems, RF systems, and power systems to ensure safe and reliable operation of the vehicle. In your first 6 months you will work with your team to develop core pieces of the FPGA architecture such as the strategies for fault tolerance, real-time control, high-speed data routing, and telemetry downlink. In your first year you will implement larger and more complex FPGA systems and begin verifying your code using both software and hardware in the loop simulators. In your first two years you will operate your code on multiple spacecraft, demonstrating robust performance in demanding missions.

Responsibilities

  • Own the architecture and implementation of critical programmable logic systems across the spacecraft that support vehicle networking, RF systems, and real-time control of all spacecraft subsystems
  • Implement these architectures in RTL using VHDL and SystemVerilog
  • Verify and validate FPGA designs using a mix of simulation, bench-testing, and Hardware In The Loop testbeds
  • Support integration, test, and troubleshooting efforts for FPGA designs across all levels of the spacecraft development and manufacturing
  • Develop the tools and infrastructure to support rapid, high-reliability FPGA solutions across all subsystems

Qualifications

  • Bachelor's degree in computer science, computer engineering, electrical engineering, math, or a STEM discipline or 3+ years of professional experience in software development
  • 3+ years working with complex FPGA designs spanning digital, mixed signal, or RF applications
  • Development experience with VHDL or SystemVerilog

Nice to Have

  • Experience integrating logic onto Xilinx SoC platforms
  • Experience with digital signal processing (DSP) fundamentals and implementing complex DSP logic and software defined radios on FPGAs
  • Experience implementing high-speed SERDES interfaces such as Ethernet, PCIe, and JESD204C.
  • Experience with standard bus and streaming protocols such as AXI and AXI-Stream
  • Experience with evaluating and integrating vendor/third party IP
  • Experience with common scripting languages such as Python, TCL, and Bash
  • Experience with Linux systems programming and driver development
  • Experience with continuous integration and continuous delivery systems
  • Experience building or working with hard real-time embedded systems (bare-metal or RTOS)
  • Basic knowledge of electronics, computer architecture, and control systems
  • Experience with software verification and testing methods
  • Experience with software and network performance analysis and debugging

Compensation and Benefits:

  • Base salary range for this role is $120,000 – $225,000 + equity in the company
  • Salary will be based on several factors including, but not limited to: knowledge and skills, education, and experience level
  • Comprehensive benefits package including paid time off, medical/dental/vision/ coverage, life insurance, paid parental leave, and many other perks

If you don't meet 100% of the preferred skills and experience, we encourage you to still apply! Building a spacecraft unlike any other requires a team unlike any other and non-traditional career twists and turns are encouraged!

If you need a reasonable accommodation as part of your application for employment or interviews with us, please let us know.

Export Compliance

As defined in the ITAR, "U.S. Persons" include U.S. citizens, lawful permanent residents (i.e., Green Card holders), and certain protected individuals (e.g., refugees/asylees, American Samoans). Please consult with a knowledgeable advisor if you are unsure whether you are a "U.S. Person."

The person hired for this role will have access to information and items controlled by U.S. export control regulations, including the export control regulations outlined in the International Traffic in Arms Regulation (ITAR). The person hired for this role must therefore either be a "U.S. person" as defined by 22 C.F.R. § 120.15 or otherwise eligible for a federally issued export control license.

Equal Opportunity

K2 Space is an Equal Opportunity Employer; employment with K2 Space is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.


K2 Space logo

About K2 Space

Sourced by ZipRecruiter

Industry

Guided missile and space vehicle manufacturing

Company size

11 - 50 Employees

Headquarters location

Los Angeles, CA, US

Year founded

2022