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Android Automotive Jobs in California (NOW HIRING)

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$10

$60

$82

How much do android automotive jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for android automotive in California is $60.33, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $69.52 per hour, depending on experience, location, and employer.

What are typical daily responsibilities for someone working in an Android Automotive role?

Daily responsibilities in an Android Automotive role often include designing, developing, and testing software components for vehicle infotainment systems based on the Android platform. You’ll collaborate with cross-functional teams, such as hardware engineers, UX/UI designers, and QA specialists, to implement and debug features that meet automotive standards. Regular work may involve integrating third-party apps, optimizing performance, ensuring the software meets safety and compliance requirements, and troubleshooting issues reported from in-vehicle testing. Working in this field offers variety and the chance to contribute to cutting-edge automotive technology while developing expertise in both embedded and mobile platforms.

What are the key skills and qualifications needed to thrive in the Android Automotive position, and why are they important?

To thrive in Android Automotive, you need strong proficiency in Java and Kotlin programming, experience with Android SDK, and a background in embedded systems or automotive software development. Familiarity with tools such as Android Studio, CAN bus protocols, and knowledge of automotive safety standards like ISO 26262 is often required. Excellent problem-solving, teamwork, and communication skills set top candidates apart. These combined abilities ensure safe, efficient, and innovative development of automotive infotainment and connectivity solutions.

What is an Android Automotive job?

An Android Automotive job typically involves developing, integrating, or maintaining software for Android Automotive OS (AAOS), Google's in-vehicle infotainment platform. Professionals in this field work on building apps, optimizing system performance, and ensuring compliance with automotive standards. Roles may vary from software engineering to UX design, system integration, or testing. Strong knowledge of Android SDK, automotive protocols, and embedded systems is often required.

What are the most commonly searched types of Android Automotive jobs in California? The most popular types of Android Automotive jobs in California are:
What are popular job titles related to Android Automotive jobs in California? For Android Automotive jobs in California, the most frequently searched job titles are:
What job categories do people searching Android Automotive jobs in California look for? The top searched job categories for Android Automotive jobs in California are:
What cities in California are hiring for Android Automotive jobs? Cities in California with the most Android Automotive job openings:
Android Automotive jobs near you
Infographic showing various Android Automotive job openings in California as of July 2026, with employment types broken down into 47% Full Time, 13% Part Time, and 40% Contract. Highlights an 100% In-person job distribution, with an average salary of $125,486 per year, or $60.3 per hour.
Embedded AI Engineer - Android Automotive (On-Device Intelligence)

Embedded AI Engineer - Android Automotive (On-Device Intelligence)

Applied Intuition

Sunnyvale, CA • On-site

$153K - $201K/yr

Full-time

Posted 17 days ago

Job description

Job Summary:
Applied Intuition is a Silicon Valley company focused on powering the future of physical AI. The Embedded AI Engineer will be responsible for the end-to-end lifecycle of embedded ML systems on the Android Automotive platform, ensuring models operate safely and predictably in real-world conditions.
Responsibilities:
• Deploy and run production-grade ML inference and learning systems on Android Automotive (AAOS)
• Implement on-device multimodal LLMs, including schema design and safe dispatch to local vehicle APIs
• Integrate models using TensorFlow Lite, ONNX Runtime, or specialized vendor SDKs
• Profile and optimize models for strict latency, memory, power, and thermal budgets
• Instrument runtime performance across CPU, GPU, and NPU acceleration layers
• Design safety boundaries and guardrails for model outputs, including tool-call allowlists and fallback logic
• Interface directly with vehicle signals, sensors, and system services using C++ and JNI
Qualifications:
Required:
• BS, MS, or PhD in Computer Science, Electrical Engineering, or a related technical field
• 3+ years of experience shipping ML inference on embedded, mobile, or automotive platforms
• Strong proficiency in C++ and experience with native Android integration (JNI)
• Expertise in model optimization techniques such as quantization, pruning, and compilation
• Experience integrating LLM function calling or tool execution with structured outputs
• Hands-on experience with Android system services or Android Automotive OS (AAOS)
• Deep understanding of edge constraints including real-time behavior and memory pressure
Preferred:
• Experience with Snapdragon Automotive, ARM Ethos, or specialized NPU pipelines
• Background in running quantized LLMs on-device using llama.cpp or TFLite transformers
• Familiarity with functional safety concepts (ISO 26262), sandboxing, or policy enforcement
• Experience bridging cloud-trained models to resource-constrained embedded runtimes
Company:
Applied Intuition provides software infrastructure to safely develop, test, and deploy autonomous vehicles
 at scale. Founded in 2017, the company is headquartered in Mountain View, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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