ZipRecruiter

Log In

1

Embedded Machine Learning Engineer Jobs in Sunnyvale, CA

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

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

$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 ...

Quantcast

Machine Learning Engineer

San Francisco, CA · On-site

$151.30 - $178/hr

As a Machine Learning Engineer you care about the health and maintainability of our systems and the velocity of the engineering teams. You explore data, research new algorithms, experiment with proof ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine learning research into scalable, production-ready solutions. You will collaborate closely with cross ...

Plenful

Machine Learning Engineer

San Francisco, CA · On-site

About the Role We're looking for a Machine Learning Engineer to design, build, and deploy production-grade ML systems that power the next generation of Plenful's AI platform. You'll own the end-to ...

Articul8

Machine Learning Engineer

Dublin, CA · On-site

$90 - $130/hr

We are seeking machine learning engineers to join our team full-time. As part of your role, you will help us build pipelines of data collection, data extraction, data filtering/synthetic data ...

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

Unitytech

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

Altera

Machine Learning Engineer

San Jose, CA · On-site

About the Role We are seeking a Machine Learning Engineer to help drive the development,optimizationand deploymentof Altera FPGA Compiler. In this role, you will work at the intersection of machine ...

Articul8

Machine Learning Engineer

Dublin, CA · On-site

We are seeking machine learning engineers to join our team full-time. As part of your role, you will help us build pipelines of data collection, data extraction, data filtering/synthetic data ...

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

previous page

Showing results 41-60

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 Aug 16, 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 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 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 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 July 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $180,019 per year, or $86.5 per hour.

Machine Learning Engineer

Nace AI

Palo Alto, CA • On-site

Full-time

Re-posted 2 days ago

Job description

Job Summary:
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 involves designing and maintaining ML systems, collaborating with cross-functional teams, and enhancing existing models with the latest advancements in machine learning.
Responsibilities:
• Design, build, and maintain end-to-end ML systems, including synthetic data pipelines, model training, debugging, and performance evaluation.
• Fine-tune large language models (LLMs) and implement meta-learning methods to enhance model generalization and efficiency.
• Improve existing Nace.AI models by incorporating advancements from recent ML research.
Qualifications:
Required:
• Hands-on experience training and fine-tuning large language models (LLMs) and vision-language models (VLMs), including practical work with pre-training, instruction tuning, and alignment techniques (GRPO,RLHF/DPO/PPO).
• Hands-on Experience with Deep Learning Models, especially Transformers.
• Ability to translate cutting-edge research from papers into clean, production-ready code (Paper to Code).
• Proven experience scaling inference infrastructure for LLMs/VLMs, including expertise in model serving frameworks like vLLM, TGI.
• Proficient in Python with a strong track record of building substantial projects.
• Solid foundation in computer science fundamentals (data structures, algorithms, design patterns).
• BS degree in CS or related technical field.
• Solid Experience with ML frameworks and libraries (PyTorch, TensorFlow).
• Self-starter comfortable working in a fast-paced, dynamic environment.
Preferred:
• MS/PhD in CS or related technical field.
• Familiarity with data processing stacks such as Spark and Airflow.
• Experience with multi-node GPU training.
• Contributor to open-source ML projects.
• Deep knowledge in Linear Programming.
• Experience with advanced NLP and Multimodal post-training experience (e.g., model distillation, quantization, deployment optimization).
• Experienced in inference time optimization, deep understanding of LLM serving optimizations for LLMs/VLMs.
• Hands on experience with quantization techniques (AWQ, GPTQ, FP8/GGUF).
Company:
Enterprise AI product & research company, building long-horizon reasoning models and agents. Founded in 2024, the company is headquartered in Palo Alto, USA, with a team of 11-50 employees. The company is currently Early Stage.

Apply