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Embedded Ai Engineer Jobs in Washington (NOW HIRING)

Senior Staff AI Engineer

Columbia, MD ยท On-site

$101K - $139K/yr

Renesas Electronics is an embedded semiconductor solution provider seeking a highly skilled Senior Staff AI Engineer to lead their Edge AI Applications Lab. The role involves managing R&D projects ...

Embedded Engineer

Columbia, MD ยท On-site

$129K - $170K/yr

Overview BigBear.ai is seeking an Embedded Engineer to join and assist and meet mission needs for our government customer. At BigBear.ai, you'll work alongside some of the brightest minds in ...

Embedded Engineer

Columbia, MD ยท On-site

$129K - $170K/yr

Overview BigBear.ai is seeking an Embedded Engineer to join and assist and meet mission needs for our government customer. At BigBear.ai, you'll work alongside some of the brightest minds in ...

Overview BigBear.ai is seeking an Embedded Engineer to join and assist and meet mission needs for our government customer. At BigBear.ai, you'll work alongside some of the brightest minds in ...

Senior Staff AI Engineer

Columbia, MD

$103K - $142K/yr

Work with other AI and embedded engineers to optimize and deploy AI models suitable for microcontrollers (MCUs) and embedded platforms. * Manage a variety of projects both technically and ...

Senior Staff AI Engineer

Columbia, MD

$103K - $142K/yr

Work with other AI and embedded engineers to optimize and deploy AI models suitable for microcontrollers (MCUs) and embedded platforms. * Manage a variety of projects both technically and ...

Senior Staff AI Engineer

Columbia, MD ยท On-site

$103K - $142K/yr

Work with other AI and embedded engineers to optimize and deploy AI models suitable for microcontrollers (MCUs) and embedded platforms. * Manage a variety of projects both technically and ...

Forward Deployed AI Engineer, Senior

Rockville, MD ยท On-site

$108K - $146K/yr

The Forward Deployed AI Engineer will serve as the AI expert embedded across multiple client projects, partnering with engineering teams, business stakeholders, and leadership to advance AI adoption ...

Computer Vision AI Engineer

Mclean, VA ยท On-site

$99K - $225K/yr

Computer Vision AI Engineer The Opportunity: Booz Allen is seeking an innovative and experienced AI ... Experience with embedded systems programming in C, C++, or Rust * Experience in GPU programming ...

Computer Vision AI Engineer

Mclean, VA ยท On-site

$99K - $225K/yr

R0244633 Computer Vision AI Engineer The Opportunity: Booz Allen is seeking an innovative and ... Experience with embedded systems programming in C, C++, or Rus t * Experience in GPU programming ...

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Showing results 1-20

Embedded Ai Engineer information

See Washington salary details

$79.3K

$173.7K

$197.1K

How much do embedded ai engineer jobs pay per year?

As of Jul 26, 2026, the average yearly pay for embedded ai engineer 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 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.
What are popular job titles related to Embedded Ai Engineer jobs in Washington? For Embedded Ai Engineer jobs in Washington, the most frequently searched job titles are:
What cities in Washington are hiring for Embedded Ai Engineer jobs? Cities in Washington with the most Embedded Ai Engineer job openings:
Infographic showing various Embedded Ai Engineer job openings in Washington as of July 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution, with an average salary of $173,722 per year, or $83.5 per hour.
Manager, Forward-Deployed AI Engineer - AI Mobilization & Transformation

Manager, Forward-Deployed AI Engineer - AI Mobilization & Transformation

MasterCard

Arlington, VA โ€ข On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago


Job description

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build asustainableeconomy where everyone can prosper. We support a wide range of digital payments choices, making transactionssecure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Manager, Forward-Deployed AI Engineer - AI Mobilization & TransformationOverview
The Manager, Forward-Deployed AI Engineer serves as Mastercard's embedded AI transformation leader, partnering directly with business units to identify high-value opportunities, develop production-grade AI solutions, and mobilize teams to adopt new ways of working.
Reporting to the Director, Forward-Deployed AI Engineer - AI Mobilization & Transformation, this role combines deep technical expertise with change leadership. Rather than building solutions in isolation, you will work alongside business teams to solve real problems, demonstrate the art of the possible, and develop internal capability through hands-on engagement.
Success is measured not only by the solutions delivered, but by the number of leaders, engineers, analysts, and teams equipped to independently leverage AI, agents, and multi-agent systems in their daily work.
The Role
Mobilizing AI Adoption Through Bespoke Engagements
Embed within business units to identify strategic workflow, productivity, and decision-making opportunities where AI can create measurable value.
Lead AI Transformation Engagements that combine discovery, solution design, implementation, and capability building.
Build high-impact use cases that serve as showcase examples for broader organizational adoption.
Translate business challenges into practical applications of AI, agents, and multi-agent orchestration.
Create reusable playbooks, patterns, and training assets that accelerate adoption across the enterprise.
Partner with business leaders to demonstrate measurable outcomes and establish local AI champions.
Support the identification and delivery of high-value AI opportunities across business functions.
Contribute reusable assets and implementation patterns that accelerate future engagements.
Building While Teaching
Design and deploy production-ready AI assistants, agents, and orchestration frameworks that solve real business problems.
Use each engagement as a live learning environment where business and technical teams learn modern AI practices through delivery.
Coach engineers, analysts, product managers, knowledge workers, and operational teams on AI-first ways of working.
Establish a "train-the-trainer" model that enables local teams to continue scaling capabilities after engagements conclude.
Facilitate hands-on workshops focused on prompt engineering, agent design, workflow automation, Copilot practices, and AI-assisted development.
Develop practitioners capable of independently applying AI tools and techniques within their teams.
Promote knowledge sharing and adoption of established AI best practices.
Advancing Agentic Transformation
Architect and implement solutions leveraging Copilot Studio, Azure AI, agent frameworks, orchestration systems, and enterprise platforms.
Develop multi-agent solutions that automate complex business processes and decision flows.
Introduce modern engineering practices including AI-assisted software development, evaluation frameworks, observability, and governance.
Establish proven reference architectures and patterns that can be replicated across business units.
Help business teams evolve from experimentation to operationalized AI solutions.
Apply established AI patterns and frameworks to accelerate solution delivery and adoption.
Evaluate emerging AI capabilities and assist in translating them into practical business applications.
Capturing and Scaling Organizational Learning
Document emerging patterns, successful use cases, implementation approaches, and lessons learned.
Build an enterprise library of AI-enabled workflows, agents, and transformation stories.
Identify adoption barriers and design interventions that accelerate organizational readiness.
Contribute to enterprise readiness metrics by measuring adoption, productivity gains, capability growth, and business impact.
Create a feedback loop between field engagements, engineering teams, and organizational readiness programs.
Capture reusable assets, implementation approaches, and best practices from engagements.
Share lessons learned to improve future AI transformation efforts across the organization.
All About You
Extensive software engineering experience with a track record of building and deploying production-grade systems.
Deep experience with AI technologies including LLMs, agent frameworks, RAG architectures, orchestration patterns, and AI application development.
Experience building and deploying enterprise AI solutions that deliver measurable business outcomes.
Strong facilitation and coaching abilities, with experience educating technical and non-technical audiences.
Comfortable working directly with business stakeholders to identify opportunities and redesign workflows.
Proven ability to influence organizational change through hands-on partnership and delivery.
Experience mentoring and developing technical talent through real-world project engagements.
Strong understanding of responsible AI, governance, risk management, and production monitoring practices.
Ability to translate complex technical concepts into practical business value and adoption strategies.
Experience supporting cross-functional initiatives that combine AI adoption, workflow transformation, and capability development.
Demonstrated ability to build relationships and influence stakeholders across technical and business teams.
Experience documenting and sharing repeatable patterns, practices, or implementation approaches.
Strong communication skills with the ability to explain AI concepts to both technical and non-technical audiences.
Experience driving adoption of new technologies through hands-on engagement and coaching.
Experience with Copilot Studio, Azure AI, GitHub Copilot, Claude Code, or equivalent platforms preferred.
Financial services, payments, or enterprise transformation experience preferred.
Passion for developing others and creating sustainable capability within organizations.
Success in This Role
Success is not measured by the number of agents you build. Success is measured by the number of teams that can build without you.
You leave behind:
New organizational capability.
Repeatable AI patterns.
Trained champions and practitioners.
Demonstrated business value.
Sustainable adoption of AI-first ways of working.
Increased confidence and proficiency in applying AI across day-to-day work.
Reusable assets and implementation practices that accelerate future adoption.Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility


All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

  • Abide by Mastercard's security policies and practices;

  • Ensure the confidentiality and integrity of the information being accessed;

  • Report any suspected information security violation or breach, and

  • Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.

Pay Ranges

Purchase, New York: $161,000 - $266,000 USDArlington, Virginia: $161,000 - $266,000 USDAtlanta, Georgia: $140,000 - $231,000 USD