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Embedded Machine Learning Engineer Jobs in Sunnyvale, CA

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

Apple

Machine Learning Engineer (Search)

Cupertino, CA · On-site

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

Apple Inc.

Machine Learning Engineer

Sunnyvale, CA · On-site

$150.40 - $277.60/hr

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Eve

Machine Learning Engineer

San Francisco, CA

We're hiring an Machine Learning Engineer as the volume and complexity of legal AI workflows in our system scale rapidly. As more firms rely on Eve to automate high-stakes legal work - from intake ...

Proofpoint

Machine Learning Engineer

Sunnyvale, CA · On-site

Machine Learning Engineer Location : Sunnyvale, CA, USA, Hyderabad, A.P., India , Athens, Greece Role Overview: Proofpoint is building the next generation of AI-powered security systems to protect ...

New

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around ...

Apple

Machine Learning Engineer

Santa Clara, CA

$150K - $277K/yr

Our team comprises a diverse range of backgrounds, including applied machine learning engineers with a focus on ML and LLM, and experienced distributed systems engineers. As such, we are seeking ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

Nace AI is a company focused on machine learning solutions, and they are seeking a Machine Learning Engineer to translate cutting-edge research into scalable, production-ready solutions. The role ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

$150K - $277K/yr

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$184K - $324K/yr

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

Bee Genius is building the future of work and is seeking an AI/Machine Learning Engineer to join their team. The role involves developing and implementing machine learning models and algorithms to ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Sunnyvale, CA

Embedded Machine Learning Engineer information

See Sunnyvale, CA salary details

$82.2K

$180K

$204.2K

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

As of Sep 6, 2026, the average yearly pay for embedded machine learning engineer in Sunnyvale, CA is $180,019.00, according to ZipRecruiter salary data. Most workers in this role earn between $154,300.00 and $203,000.00 per year, depending on experience, location, and employer.

What does an embedded machine learning engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

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

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by embedded machine learning engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Sunnyvale, CA?

For Embedded Machine Learning Engineer jobs in Sunnyvale, CA, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning Engineer jobs in Sunnyvale, CA look for?

The top searched job categories for Embedded Machine Learning Engineer jobs in Sunnyvale, CA are:

What cities near Sunnyvale, CA are hiring for Embedded Machine Learning Engineer jobs?

Cities near Sunnyvale, CA with the most Embedded Machine Learning Engineer job openings:

Embedded Machine Learning Engineer jobs near you
Infographic showing various Embedded Machine Learning Engineer job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $180,019 per year, or $86.5 per hour.

Machine Learning Engineer

MBZUAI (Mohamed bin Zayed University of Artificial Intelligence)

Sunnyvale, CA • On-site

Full-time

Re-posted 13 days ago

Job description

Job Summary:
MBZUAI is a dedicated research lab for building, understanding, using, and risk-managing foundation models. As a Machine Learning Engineer, you will develop and implement innovative machine learning models, collaborate with cross-functional teams, and contribute to MBZUAI's mission of driving impactful AI discoveries.
Responsibilities:
• Collaborate with Research teams to understand technologies, adapting and integrating them into codebase.
• Develop and implement systems to support the lifecycle of machine learning models, such as data preprocessing, pre-training, post-training, evaluation and so on, especially foundation models.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Contribute to research papers and represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation.
• Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.
Qualifications:
Required:
• Bachelor’s degree or equivalent practical experience.
• 3 years of experience in software engineering, including experience with Machine Learning (ML) models, ML infrastructure, Natural Language Processing or Computer Vision.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
• Excellent problem-solving and troubleshooting skills to address complex technical challenges.
• Effective communication and collaboration skills to work with cross functional teams.
Preferred:
• Master's degree or PhD in Computer Science or related technical field.
• 2 years of experience with improving performance during large scale data processing.
• Hands-on experience with LLM algorithms, such as Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF).
• Excellent data analysis skills.
Company:
Official account of Mohamed bin Zayed University of Artificial Intelligence. Dedicated to research, innovation, and empowering brilliant minds in AI. Founded in 2019, the company is headquartered in Abu Dhabi, ARE, with a team of 51-200 employees. The company is currently Growth Stage.

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