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Senior Embedded Machine Learning Jobs in Portland, OR

Pwc

CTIO - AI Engineer- Senior Manager

Portland, OR

$91K - $321K/yr

... machine learning algorithms and predictive modeling techniques - Collaborating with clients to validate outcomes and incorporate feedback into data solutions - Directing teams through complex ...

Apple

SerDes Micro Architect

Beaverton, OR

... Machine Learning concepts Experience in firmware or embedded software development is a plus Minimum Qualifications BS degree in technical discipline with minimum 10 years of relevant experience.

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All JobsEmbedded Machine Learning JobsSenior Embedded Machine Learning JobsSenior Embedded Machine Learning Jobs in Portland, OR

Senior Embedded Machine Learning information

See Portland, OR salary details

$80.1K

$153.5K

$205.2K

How much do senior embedded machine learning jobs pay per year?

As of Aug 21, 2026, the average yearly pay for senior embedded machine learning in Portland, OR is $153,533.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $172,300.00 per year, depending on experience, location, and employer.

What does a senior embedded machine learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.

What are the key skills and qualifications needed to thrive as a senior embedded machine learning engineer?

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What are some common challenges faced by senior embedded machine learning engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What are the most commonly searched types of Embedded Machine Learning jobs in Portland, OR?

The most popular types of Embedded Machine Learning jobs in Portland, OR are:

Senior Embedded Machine Learning jobs near you

Senior Security Engineer, RTOS and Virtualization

Nvidia

Hillsboro, OR

$124K - $171K/yr

Full-time

Posted 10 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies

Job description

NVIDIA is a leading artificial intelligence computing company, and we are paving the way with innovations in self-driving cars, machine learning, supercomputing, gaming, and visualization. We give automakers, tier-1 suppliers, automotive research institutions, and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for self-driving vehicles. Our unified computing architecture enables training deep neural networks in the data center, and then seamlessly runs them on NVIDIA DRIVE Platforms inside the vehicle.

Within NVIDIA DRIVE Software, the Hypervisor and RTOS Team contributes significantly to NVIDIA's advancement in artificial intelligence and autonomous vehicles. Our mission is to manage system resource sharing and separation while fulfilling real-time, safety, and security needs. We design Hypervisor and RTOS focusing on automotive quality, safety, and security required by the real-time, highly reliable system parts of leading Autonomous Vehicles. We are hiring now for the position of Senior Security Engineer, RTOS and Virtualization

What you'll be doing:

  • Lead security engineering for RTOS, hypervisor, and embedded virtualization technologies across design, implementation, review, and verification.

  • Collaborate on CPU and SoC architecture, including privilege levels, memory protection, DMA, interrupts, boot flows, debug controls, and hardware isolation.

  • Build and implement defensive features such as strong partitioning, least-privilege access, secure communication, fault containment, secure updates, and recovery from malicious inputs.

  • Perform threat modeling and automotive TARA, and connect risks, mitigations, requirements, tests, and evidence to security and safety standards.

  • Review low-level C/C++ code, investigate vulnerabilities, build fuzzing and security test infrastructure, and drive fixes into production.

What we need to see:

  • 8+ years of hands-on experience in systems, embedded, platform, product, or automotive security.

  • BSEE/ BSCS degree or equivalent experience

  • Experience securing RTOS, hypervisor, kernel, firmware, boot, driver, or other privileged software.

  • Strong C/C++ skills, with focus on memory safety, concurrency, resource ownership, privilege boundaries, and isolation.

  • Familiarity with CPU and SoC security concepts including MMU/SMMU or IOMMU, DMA, interrupts, boot, debug, and hardware-backed isolation.

  • Experience with threat modeling, vulnerability analysis, exploitability assessment, fuzzing, static or dynamic analysis, and security remediation.

  • Familiarity with automotive cybersecurity, safety, or process standards such as ISO/SAE 21434, UN R155, ISO 26262 interfaces, or Automotive SPICE.

Ways to stand out from the crowd:

  • Drove adoption of Rust, Ada/SPARK, formal methods, or other memory-safe and analyzable systems approaches.

  • Built capability-based or ownership-based security models for low-level systems.

  • Built security automation, fuzzing infrastructure, review agents, or AI-assisted tools used by engineering teams.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 15, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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