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Embedded Ai Engineer Jobs in California (NOW HIRING)

Teserac, Inc.

AI Engineer

Santa Clara, CA · On-site

An embedded AI teammate serves as every operator's always-on co-pilot: detecting anomalies, correlating events, and surfacing recommendations 24/7. We are seeking an AI/ML Engineer who is excited to ...

Teserac, Inc.

AI Engineer

Santa Clara, CA · On-site

An embedded AI teammate serves as every operator's always-on co-pilot: detecting anomalies, correlating events, and surfacing recommendations 24/7. We are seeking an AI/ML Engineer who is excited to ...

Nexxa.ai

Applied AI Engineer

San Francisco, CA · On-site

Role Overview We're looking for Applied AI Engineers to work as forward deployed directly with ... Prior experience in consulting , technical solutions , professional services , or customer-embedded ...

h2o.ai

Senior AI Engineer

San Francisco, CA · On-site

$180 - $280/hr

This is a hands‑on engineering role embedded within a customer‑facing field team, meaning your ... Design and build agentic AI systems and multi‑agent frameworks that automate complex ...

Teserac, Inc.

AI Engineer

Sunnyvale, CA · On-site

$100 - $130/hr

An embedded AI teammate serves as every operator's always-on co‑pilot: detecting anomalies, correlating events, and surfacing recommendations 24/7. We are seeking an AI/ML Engineer who is excited ...

h2o.ai

Senior AI Engineer

San Francisco, CA · On-site

$123K - $169K/yr

This is a hands-on engineering role embedded within a customer-facing field team, meaning your work ... Agentic AI & LLM Engineering * Design and build agentic AI systems and multi-agent frameworks that ...

h2o.ai

Senior AI Engineer

San Francisco, CA · On-site

$123K - $169K/yr

This is a hands-on engineering role embedded within a customer-facing field team, meaning your work ... Agentic AI & LLM Engineering * Design and build agentic AI systems and multi-agent frameworks that ...

Roku

Software Engineer, Embedded Agentic AI

San Jose, CA · On-site

$170K - $210K/yr

About the team Roku TV is where embedded systems, media experiences, and intelligent software come ... This is a hands-on engineering role for someone who treats AI agent design as an engineering ...

Roku

Software Engineer, Embedded Agentic AI

San Jose, CA · On-site

$170K - $210K/yr

About the team Roku TV is where embedded systems, media experiences, and intelligent software come ... This is a hands-on engineering role for someone who treats AI agent design as an engineering ...

Precision Castparts Corp.

AI Engineer

Santa Ana, CA · On-site

$96K - $115K/yr

AI Engineer Country United States of America State / County California City Santa Ana Division ... This role will build solutions that are embedded in daily workflows and deliver measurable business ...

t0

AI Engineer

San Francisco, CA · On-site

$150 - $230/hr

... embedded finance at a global scale. Proudly founded in Melbourne, we have a team of over 2,300 of ... We leverage cutting‑edge AI tooling across the spectrum: from prompt engineering and in‑context ...

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All JobsEmbedded Ai Engineer JobsEmbedded Ai Engineer Jobs in California

Embedded Ai Engineer information

See California salary details

$69.1K

$151.4K

$171.7K

How much do embedded ai engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for embedded ai engineer in California is $151,375.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,800.00 and $170,700.00 per year, depending on experience, location, and employer.

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 are the key skills and qualifications needed to thrive as an embedded AI engineer?

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 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 California?

For Embedded Ai Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Embedded Ai Engineer jobs in California look for?

The top searched job categories for Embedded Ai Engineer jobs in California are:

What cities in California are hiring for Embedded Ai Engineer jobs?

Cities in California with the most Embedded Ai Engineer job openings:

Embedded Ai Engineer jobs near you
Infographic showing various Embedded Ai Engineer job openings in California as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $151,375 per year, or $72.8 per hour.

(US) Edge AI Architect- CUDA / C++ / Computer Vision

Codvo.ai

Santa Clara, CA • On-site

$203K/yr

Full-time

Re-posted 23 days ago

Job description

Job Description: Edge AI Architect - CUDA / C++ / Computer Vision
Experience Level: 10+ Years
Department: Edge AI & Embedded Systems
About the Role:
We are looking for a highly motivated and technically proficient Edge AI Engineer with a strong background in Edge AI devices, computer vision algorithms, and AI model deployment in the MedTech domain. This role is pivotal in developing and optimizing AI-powered medical devices that operate at the edge, ensuring performance, reliability, and compliance with healthcare standards.
Key Responsibilities:
• Design, develop, and optimize AI models for deployment on Edge AI devices in medical applications.
• Implement and evaluate computer vision algorithms for real-time video and image analysis.
• Collaborate with cross-functional teams to integrate AI solutions into embedded systems and medical devices.
• Ensure compliance with SaMD classification, regulatory standards, and quality processes.
• Document design specifications, test protocols, and validation reports in accordance with regulatory requirements.
• Communicate technical findings and project updates effectively to stakeholders.
Required Qualifications:
• Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Biomedical Engineering, or related field.
• 8+ years of experience in AI engineering, preferably in medical devices or healthcare technology.
• Strong experience with Edge AI hardware platforms (e.g., NVIDIA Jetson, Google Coral, Intel Movidius).
• Strong experience in CUDA, C++ writing drivers with contract manufactured Edge AI devices with custom GPU configuration
• Proficiency in computer vision frameworks (e.g., OpenCV, TensorFlow, PyTorch) and model optimization tools.
• AI/ML Acumen (Crucial) Required: Strong LLM, RAG, agentic architecture understanding
• Understanding of SaMD regulations, ISO 13485, IEC 62304, and related standards.
• Experience with embedded systems development and real-time processing.
• Excellent verbal and written communication skills.
Nice to Have:
• Experience testing or developing AI systems for surgical applications.
• Familiarity with test data validation for computer vision and video-based AI models.
• Knowledge of risk management processes (ISO 14971) and cybersecurity standards in healthcare.
• Experience with cloud-edge integration and CI/CD pipelines for AI deployment.

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