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Embedded Machine Learning Jobs in San Jose, CA (NOW HIRING)

E-Space

AI / Embedded ML Engineer

Saratoga, CA · On-site

$145K - $190K/yr

As an AI / Embedded ML Engineer, you will be responsible for the full lifecycle of AI/machine learning on resource-constrained hardware, including data ingestion, model development, optimization, and ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

What we're seeking A visionary Machine Learning Engineer to join our founding team who will help ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

E-Space

AI / Embedded ML Engineer

Saratoga, CA · On-site

$145K - $190K/yr

The AI / Embedded ML Engineer will be responsible for the full lifecycle of AI/machine learning on resource-constrained hardware, including data ingestion, model development, optimization, and ...

Atoms

Staff Machine Learning Engineer

San Francisco, CA · On-site

What we're seeking A visionary Machine Learning Engineer to join our founding team who will help ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

What we're seeking A visionary Machine Learning Engineer to join our founding team who will help ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

Atoms

Staff Machine Learning Engineer

San Francisco, CA · On-site

What we're seeking A visionary Machine Learning Engineer to join our founding team who will help ... Hands-on experience optimizing models for edge deployment or custom embedded GPU targets. * Deep ...

Efficient Computer

Senior Compiler Engineer

San Jose, CA · On-site

$160K - $210K/yr

The Compiler Engineer will contribute to the design and implementation of an embedded machine learning (ML) system stack and TinyML applications to run on the world's most energy-efficient ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Jobs in San Jose, CA

Embedded Machine Learning information

See San Jose, CA salary details

$82K

$179.8K

$203.9K

How much do embedded machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for embedded machine learning in San Jose, CA is $179,764.00, according to ZipRecruiter salary data. Most workers in this role earn between $154,100.00 and $202,800.00 per year, depending on experience, location, and employer.

What is an embedded machine learning?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in embedded machine learning?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

What are the most commonly searched types of Embedded Machine Learning jobs in San Jose, CA?

The most popular types of Embedded Machine Learning jobs in San Jose, CA are:

What are popular job titles related to Embedded Machine Learning jobs in San Jose, CA?

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

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

The top searched job categories for Embedded Machine Learning jobs in San Jose, CA are:

Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in San Jose, CA as of August 2026, with employment types broken down into 21% Internship, and 79% Full Time. Highlights an 100% In-person job distribution, with an average salary of $179,764 per year, or $86.4 per hour.

Senior Computer Vision/Machine Learning Engineer

One Way Ventures

Mountain View, CA • On-site

$120 - $150/hr

Other

Posted yesterday

New

Job description

About the company

Every physical good around you sat in a warehouse, and every warehouse tracks their inventory. Almost 100% of warehouses track their inventory using handheld barcode scanners or even paper and pencil, and people climbing scissor lifts. It's dangerous, slow, and full of human error, resulting in $30B of missing inventory annually... from inside their own facilities!

We're Corvus Robotics. We invented Corvus One, the world’s first warehouse inventory drones with Level 5 Autonomy®. They use AI and self-driving technology to fly up and down warehouse aisles day and night, helping companies’ and governments’ warehouses manage their inventory, a crucial operation every warehouse conducts. We're a mission-driven company improving the world’s supply chain efficiency, reducing waste, and improving human productivity in a globally essential industry. Come help scale our warehouse inventory AI drones across America!

About the role

We are seeking passionate Computer Vision / Machine Learning Software Engineers to build efficient models for production robotics with constrained compute. You'll tackle diverse business and technical challenges, implementing and deploying models across our robot fleet. Our robots generate vast amounts of sensor data and we are constantly searching for ways to use this data to provide customers with deeper insights and to enhance our robots’ environmental awareness. We value problem-solving, innovation, and continuous learning, and we encourage exploring new technologies to advance our machine learning capabilities.

  • US work authorization preferred, can sponsor visas

  • Location: In-office hybrid (Mountain View, CA)

Join our team and help shape the future of robotics and machine learning!

What you’ll do

  • Develop solutions for advanced computer vision tasks, including:

    • Monocular and stereo depth estimation

    • Learning-based structure-from-motion

    • 3D occupancy networks

    • Scene understanding

    • Object detection

  • Optimize performance, accuracy, and speed of compute-constrained models

  • Collaborate with cross-functional teams to deploy CV/ML models into production

  • Manage and improve ML pipelines and infrastructure for dataset management, training, and deployment

  • Participate in R&D initiatives (20% of time) to experiment with state-of-the-art techniques

  • Drive business value by leveraging your work across robotics, software, and deployment teams

Must have

  • Adaptive and desire to assume responsibility in a fast-paced startup environment

  • 5+ years of industry experience in Computer Vision / Machine Learning, Python/PyTorch

  • Expertise in 2D and 3D computer vision techniques

  • Proficiency with Linux, Git, AWS/GCP, and CI/CD workflows

  • Experience in performance engineering for deep neural networks (both training and inference)

  • Knowledge of model optimization techniques for embedded systems, including knowledge distillation, model quantization, and network pruning

Nice to have

  • Experience with C/C++

  • Familiarity with ROS (Robot Operating System)

  • Knowledge of model deployment frameworks (e.g., TensorRT, RKNN, OpenVINO, ONNX, CoreML)

  • Experience with TypeScript/JavaScript and Django

  • Experience with data labelers, tooling, and data management

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