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Embedded Ai Engineer Jobs in Redmond, WA (NOW HIRING)

Senior AI Engineer - Privacy

Bellevue, WA ยท On-site

$117.90K - $162K/yr

Embedded within the Data & Intelligence organization's Privacy practice, this engineer will apply ... AI Agent & LLM Engineering * Design and build multi-agent systems, orchestration layers, and ...

Applied AI Engineer

Seattle, WA ยท On-site

$159.40K/yr

About the job Applied AI Engineer About Us Catalyst Labs is a leading talent agency with a ... We stand out as an agency that's deeply embedded in our clients' recruitment operations. We partner ...

Senior AI Engineer - Privacy

Bellevue, WA ยท On-site

$117.90K - $162K/yr

Embedded within the Data & Intelligence organization's Privacy practice, this engineer will apply ... AI Agent & LLM Engineering * Design and build multi-agent systems, orchestration layers, and ...

Senior AI Engineer - Privacy

Bellevue, WA ยท On-site

$117.90K - $162K/yr

Embedded within the Data & Intelligence organization's Privacy practice, this engineer will apply ... AI Agent & LLM Engineering * Design and build multi-agent systems, orchestration layers, and ...

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Embedded Systems Engineer

Redmond, WA ยท Remote

$35K - $55K/yr

This role combines embedded Linux platform engineering with C++ application development. You will ... Support AI inference runtimes (CUDA, TensorRT) from an OS and deployment perspective * Implement ...

AI ML Engineer

Bellevue, WA ยท On-site +1

Embedded within the Data & Intelligence organization's Privacy practice, this engineer will apply ... AI Agent & LLM Engineering Design and build multi-agent systems, orchestration layers, and agentic ...

AI Embedded Systems Engineer

Bothell, WA ยท On-site

$106K - $176.60K/yr

Development of data products and custom applications to support downstream AI/ML use cases ... Exceptional programming skills in at least one systems language (e.g., C, C#, Java, Go) and python.

Development of data products and custom applicationsto support downstream AI/ML use cases ... Exceptional programming skills inat least one systems language (e.g., C, C#, Java, Go) and python.

Software Engineer, Embedded Systems

Seattle, WA ยท On-site

$190K - $225K/yr

A fast-growing robotics and AI company is building intelligent automation solutions that combine ... As a Sr. Software Engineer, Embedded Systems, you will work alongside your software, mechanical and ...

Software Engineer Embedded Systems

Seattle, WA ยท On-site

$190K - $225K/yr

A fast-growing robotics and AI company is building intelligent automation solutions that combine ... As a Sr. Software Engineer, Embedded Systems, you will work alongside your software, mechanical and ...

Software Engineer, Embedded Systems

Seattle, WA ยท On-site

$190K - $225K/yr

A fast-growing robotics and AI company is building intelligent automation solutions that combine ... As a Sr. Software Engineer, Embedded Systems, you will work alongside your software, mechanical and ...

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Showing results 1-20

Embedded Ai Engineer information

See Redmond, WA salary details

$78.4K

$171.8K

$194.9K

How much do embedded ai engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for embedded ai engineer in Redmond, WA is $171,782.00, according to ZipRecruiter salary data. Most workers in this role earn between $147,300.00 and $193,800.00 per year, depending on experience, location, and employer.

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 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 popular job titles related to Embedded Ai Engineer jobs in Redmond, WA? For Embedded Ai Engineer jobs in Redmond, WA, the most frequently searched job titles are:
What job categories do people searching Embedded Ai Engineer jobs in Redmond, WA look for? The top searched job categories for Embedded Ai Engineer jobs in Redmond, WA are:
What cities near Redmond, WA are hiring for Embedded Ai Engineer jobs? Cities near Redmond, WA with the most Embedded Ai Engineer job openings:
Senior AI Engineer - Privacy

Senior AI Engineer - Privacy

Merican

Bellevue, WA โ€ข On-site

$117.90K - $162K/yr

Other

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Senior AI Engineer โ€“ Privacy

The Senior AI Engineer โ€“ Privacy will design, build, and operationalize AI and agentic systems that power Client data privacy platform at scale. Embedded within the Data & Intelligence organization's Privacy practice, this engineer will apply large language models (LLMs), retrieval-augmented generation (RAG), multi-agent orchestration, and foundation model capabilities to automate, enhance, and scale privacy operations โ€” including Data Subject Request (DSR) processing, consent management, regulatory compliance monitoring, and privacy impact assessment workflows โ€” across a customer base of over 100 million. You will collaborate with data engineers, full stack engineers, privacy product managers, and legal and compliance teams to deliver production-grade AI solutions. You will apply responsible AI principles, implement human-in-the-loop controls, and ensure audit logging and observability across AI-assisted privacy workflows. Your work will directly shape how Client meets its obligations under CCPA, CPRA, TCPA, and other state and federal privacy regulations.

AI Agent & LLM Engineering
  • Design and build multi-agent systems, orchestration layers, and agentic workflows using frameworks such as LangChain, LangGraph, Google ADK, or equivalent.
  • Develop and operationalize RAG (Retrieval-Augmented Generation) pipelines integrating LLMs (e.g. Claude, Gemini, GPT-4) into production privacy applications.
  • Implement structured prompting, decision workflows, and tool orchestration โ€” including MCP (Model Context Protocol)-based architectures โ€” for autonomous agent systems.
  • Build AI-powered automation for privacy operations including intelligent DSR routing, threshold monitoring, agentic data quality checks, and automated regulatory notifications.
  • Enable human-in-the-loop controls and escalation paths for AI-assisted decisions in sensitive privacy workflows.
Data & ML Engineering
  • Build and optimize data pipelines using Azure Data Factory, Databricks, Snowflake, or PySpark to support AI model training, fine-tuning, and inference.
  • Apply prompt engineering, few-shot learning, and fine-tuning techniques to adapt foundation models for privacy-specific use cases.
  • Implement vector databases and embedding strategies to power RAG pipelines over Client internal privacy knowledge bases and policy documents.
  • Ensure data quality, lineage, and governance standards are maintained across all AI training and inference pipelines.
Cloud & MLOps
  • Deploy and manage AI workloads on Azure or AWS, including serverless inference endpoints, container registries, and GPU/compute resources.
  • Build and maintain CI/CD pipelines for AI model deployment using GitLab or Azure DevOps, applying MLOps best practices.
  • Implement monitoring, alerting, and performance tracking for production AI models and agent systems using Splunk, AppDynamics, or Grafana.
  • Apply containerization (Docker) and orchestration (Kubernetes) to ensure scalable and reliable AI service deployments.
Responsible AI & Compliance
  • Implement responsible AI principles โ€” including fairness, transparency, and explainability โ€” across all AI systems used in privacy operations.
  • Ensure AI-assisted workflows comply with CCPA, CPRA, TCPA, and other applicable state and federal privacy regulations.
  • Design and maintain audit trails and human-in-the-loop checkpoints for AI decisions affecting consumer privacy rights.
  • Collaborate with legal, compliance, and privacy operations teams to translate regulatory requirements into AI solution guardrails and constraints.
Technical Leadership & Collaboration
  • Partner with data engineers, full stack engineers, product managers, and privacy stakeholders to deliver end-to-end AI-powered privacy solutions.
  • Mentor junior engineers on AI/ML engineering practices, agentic patterns, and responsible AI design principles.
  • Produce clear technical documentation, architecture diagrams, and model cards for AI systems in production.
  • Contribute to internal accelerators, reusable AI component libraries, and the broader engineering community of practice.

TekWissenยฎ Group is an equal opportunity employer supporting workforce diversity.


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About Merican

Sourced by ZipRecruiter

Merican is a IT Service consulting firm, specialized in Digital adoption and Business automation. With our diverse collection of skilled and committed consultants, technology companies, businesses and digital experts, we provide our subject expertise and our unique client service approach, a best-in-class global model of delivery suited to the business demands of our clients. We ensure that we implement future-oriented solutions for our clients via investments in people, solutions, technologies, competencies and infrastructure.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Columbia , MD, US

Year founded

2020

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