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Fpga Deep Learning Jobs in Silver Spring, MD (NOW HIRING)

InterImage

Image Processing SME

Fort George G Meade, MD · On-site

... FPGA engineering environment. The ideal candidate will possess deep expertise in scientific and ... Develop and validate machine learning and computer vision models for automated image analysis ...

Curtiss-Wright

Principal Hardware Engineer

Ashburn, VA · Remote

$144K - $190K/yr

... SBC), FPGA, switch, and input/output cards in 3U and 6U VPX form factors; and custom form-factor ... The ideal candidate brings deep expertise in electronic components, integrated circuitry ...

Curtiss-Wright

Principal Hardware Engineer

Ashburn, VA · Remote

$144K - $190K/yr

... SBC), FPGA, switch, and input/output cards in 3U and 6U VPX form factors; and custom form-factor ... The ideal candidate brings deep expertise in electronic components, integrated circuitry ...

Curtisswright

Principal Hardware Engineer

Ashburn, VA · Remote

$144K - $190K/yr

... SBC), FPGA, switch, and input/output cards in 3U and 6U VPX form factors; and custom form-factor ... The ideal candidate brings deep expertise in electronic components, integrated circuitry ...

Curtiss-Wright

Principal Hardware Engineer

Ashburn, VA · On-site

$144K - $190K/yr

... SBC), FPGA, switch, and input/output cards in 3U and 6U VPX form factors; and custom form-factor ... The ideal candidate brings deep expertise in electronic components, integrated circuitry ...

Curtiss-Wright

Principal Hardware Engineer

Ashburn, VA · On-site

$144K - $190K/yr

... SBC), FPGA, switch, and input/output cards in 3U and 6U VPX form factors; and custom form-factor ... The ideal candidate brings deep expertise in electronic components, integrated circuitry ...

All JobsFpga Deep Learning JobsFpga Deep Learning Jobs in Silver Spring, MD

Fpga Deep Learning information

See Silver Spring, MD salary details

$72.4K

$152K

$217.6K

How much do fpga deep learning jobs pay per year?

As of Jun 26, 2026, the average yearly pay for fpga deep learning in Silver Spring, MD is $152,023.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,200.00 and $175,200.00 per year, depending on experience, location, and employer.

What are FPGA Deep Learning engineers?

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, and why are they important?

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 Silver Spring, MD? For Fpga Deep Learning jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Fpga Deep Learning jobs in Silver Spring, MD look for? The top searched job categories for Fpga Deep Learning jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Fpga Deep Learning jobs? Cities near Silver Spring, MD with the most Fpga Deep Learning job openings:
Fpga Deep Learning jobs near you
Infographic showing various Fpga Deep Learning job openings in Silver Spring, MD as of June 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 92% Physical, 5% Hybrid, and 3% Remote job distribution, with an average salary of $152,023 per year, or $73.1 per hour.

NIST PREP Graduate Student in Computer Vision AI models for Additive Manufacturing Image Processing

Southeastern Universities Research Association

Gaithersburg, MD • On-site

$37 - $38/hr

Part-time

Posted 18 days ago

Job description

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Research Title: Computer Vision AI models for Additive Manufacturing image processing
The work will entail: The NIST Information Technology Lab (ITL) and Engineering Lab (EL) are collaborating on a project for real-time image processing for Additive Manufacturing. To handle real-time constraints, computations on Field Programmable Gate Array (FPGA) devices will need to be enabled, likely involving both traditional Computer Vision algorithms and Deep Learning models.
We plan on instrumenting a hard real-time system that can meet the time sensitive deadlines for detecting sparks from a high-speed camera that is monitoring the interaction between the melt pool and laser. There are three methodologies to consider.
  1. The camera contains a built-in FPGA that can process images as they are captured.
  2. The capture card has a slightly higher-end FPGA.
  3. The capture card can transfer image data into system memory, allowing the host system to process images using either the CPU, GPU, or a combination of both.

To this end, we are seeking a Computer Scientist who will focus on developing algorithms to process frames in real-time from a high frame rate camera. The processing algorithms may utilize the camera's built-in Field Programmable Gate Arrays (FPGA), the capture card's built-in FPGA, or traditional computer CPUs and GPUs.
Key responsibilities will include but are not limited to:
  • Develop image analysis algorithms that target the highspeed camera's FPGA.
  • Develop image analysis algorithms that target the capture card's FPGA.
  • Develop image analysis algorithms that target the traditional computer's CPU(s) and GPU(s).
  • Measure real-time throughput for developed image analysis workflows.
  • Create AI/Deep learning workflows for training AI models for analyzing images in a series.

Qualifications
  • A completed or in-process graduate degree in Computer Science, Engineering, Manufacturing, or a related field.
  • 1-2 years of relevant experience.
  • Familiarity with image analysis algorithms.
  • Familiarity with FPGA programming.
  • Familiarity with CPU and/or GPU image analysis.
  • Experience with AI/Deep learning workflows, such as LSTMs.
  • Ability to develop prototypes of tools needed to analyze data.
  • Strong oral and written communication skills.
  • US Citizen Preferred

Privacy Act StatementAuthority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
|Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated.
SURA is an Equal Opportunity Employer. We believe that no one should be discriminated against because of their differences, such as age, disability, ethnicity, gender, gender identity and expression, religion, or sexual orientation. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, or any other basis as protected by federal, state, or local law.
PREP0003758

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