ZipRecruiter

Log In

1

Embedded Machine Learning Jobs in Washington (NOW HIRING)

GRVTY

Computer Vision Engineer - Senior

Springfield, VA · On-site

$109.30K - $150.10K/yr

... and embedded systems. • Complete testing and validation of computer vision systems. • ... vision, machine learning, or closely related fields. • Proficiency in Python and its ecosystem ...

STR

Principal Signal Processing Researcher

Arlington, VA

$206K - $284K/yr

... machine learning algorithms, systems analysis, and real-time embedded processor implementation. The Algorithms, Processing and Experimentation (APEX) Group specializes in development of RF/radar ...

GRVTY

Computer Vision Engineer - Senior

Springfield, VA · On-site

$109.20K - $149.90K/yr

Optimize performance for edge devices and embedded systems. Complete testing and validation of ... Experience with machine learning utilities such as MLflow, Optuna, and DVC. What Would be Nice to ...

Howard University

Assistant Professor

Washington, DC · On-site

... Initiative and is embedded within the interdisciplinary cluster "Advancing Health through ... AI and machine learning approaches in biomedical sciences. The cluster seeks to advance ...

next page

Showing results 1-20

People also search for

All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Jobs in Washington

Embedded Machine Learning information

See Washington salary details

$79.3K

$173.7K

$197.1K

How much do embedded machine learning jobs pay per year?

As of May 31, 2026, the average yearly pay for embedded machine learning in Washington is $173,722.00, according to ZipRecruiter salary data. Most workers in this role earn between $148,900.00 and $195,900.00 per year, depending on experience, location, and employer.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in the Embedded Machine Learning position, and why are they important?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.
More about Embedded Machine Learning jobs
What are the most commonly searched types of Embedded Machine Learning jobs in Washington? The most popular types of Embedded Machine Learning jobs in Washington are:
What are popular job titles related to Embedded Machine Learning jobs in Washington? For Embedded Machine Learning jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning jobs in Washington look for? The top searched job categories for Embedded Machine Learning jobs in Washington are:
Embedded Machine Learning jobs near you

Computer Vision Engineer - Senior

GRVTY

Springfield, VA • On-site

$109.30K - $150.10K/yr

Full-time

Posted 6 days ago

Job description

Job Summary:
GRVTY is a mission-focused company dedicated to tackling national security challenges through innovative technology. They are seeking a Senior Computer Vision Engineer to design and deploy advanced computer vision systems that support critical defense operations, collaborating closely with cross-functional teams.
Responsibilities:
• Design and implement advanced vision models for tasks such as object detection, tracking, scene understanding, and activity recognition.
• Collaborate with engineering teams to integrate vision capabilities into defense systems.
• Optimize performance for edge devices and embedded systems.
• Complete testing and validation of computer vision systems.
• Contribute to system architecture, technical strategy, and full lifecycle systems engineering activities.
• Perform technical planning, system integration, verification and validation, cost and risk analyses, and supportability and effectiveness assessments.
• Conduct functional analysis, timeline analysis, trade studies, requirements allocation, and interface definition to translate customer requirements into hardware and software specifications.
• Support system development across all lifecycle phases including concept, design, fabrication, test, installation, operation, maintenance, and disposal.
• Ensure the logical and systematic conversion of customer and product requirements into total systems solutions that account for technical, schedule, and cost constraints.
• Mentor junior engineers and help define best practices for the team.
• Maintain security and compliance throughout the development lifecycle.
Qualifications:
Required:
• Active TS/SCI clearance with Polygraph eligibility.
• Bachelor’s degree in Computer Science, Data Science, or a related field; equivalent experience will be considered.
• 9+ years of experience in computer vision, machine learning, or closely related fields.
• Proficiency in Python and its ecosystem, including frameworks and libraries such as Flask, SQLAlchemy, Boto3, NumPy, and Pillow, as well as deep learning tools such as PyTorch and TensorFlow; experience with Swift (OpenStack client) is also required.
• Proficiency in writing and optimizing SQL queries for data retrieval, analysis, and management.
• Experience with modern computer vision models such as YOLO, Faster R-CNN, and Vision Transformers.
• Familiarity with OpenCV and classical computer vision techniques.
• Strong engineering fundamentals, including experience with Git, Docker, and CI/CD practices.
• Experience with machine learning utilities such as MLflow, Optuna, and DVC.
Preferred:
• Experience supporting government or defense-related programs.
• 5+ years of experience developing Python scripts for data automation, process optimization, and machine learning workflow implementation.
• Knowledge of real-time video analytics, sensor fusion, or 3D perception.
• Experience working within secure or classified development environments.
Company:
GRVTY is a defense technology company that provides software and data solutions for defense sectors. Founded in 2024, the company is headquartered in Arlington, USA, with a team of 501-1000 employees. The company is currently Late Stage.

Apply