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

Applied Industrial Technologies
Sunnyvale
Workplace: OnsiteFull timeUSD 150,000 - 250,000 annuallyFunction: Data Science & Machine LearningExperience: 3+ yearsSkills: ["Communication","Problem-solving"]

Role owning the end-to-end lifecycle of embedded ML systems for an Android Automotive platform. You will deploy production-grade ML inference and learning on AAOS, implement on-device multimodal LLMs, optimize models for strict latency/memory/power constraints, and interface with vehicle signals via C++/JNI to ensure safe, real-time on-device intelligence.

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FursaFursa
Applied Industrial Technologies
Applied Industrial Technologies
4 months ago

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

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 18 hours agoStatus: Live

Job Summary

Role owning the end-to-end lifecycle of embedded ML systems for an Android Automotive platform. You will deploy production-grade ML inference and learning on AAOS, implement on-device multimodal LLMs, optimize models for strict latency/memory/power constraints, and interface with vehicle signals via C++/JNI to ensure safe, real-time on-device intelligence.
Location: Sunnyvale
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key 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

Pay and Benefits

Salary: USD 150,000 - 250,000 annually
Perks:Health InsuranceDentalVision401kLearning Budget

Key Requirements

  • •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
Experience:3+ yearsAutomotiveEmbeddedEdge computing
Skills:CommunicationProblem-solving
Tech Stack:C++JNITensorFlow LiteONNX RuntimeAndroid Automotive OSQuantizationPruningCompilation

Company Brief

Applied Industrial Technologies
Builds software tools for autonomous vehicle development, including simulation, validation, and data infrastructure for automakers and robotics teams. Also supports defense applications with autonomy-focused testing and deployment platforms.
Industry: Developer Tools
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Headquarters: Mountain View, United States
Founded: 2017
WebsiteLinkedIn