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Senior Research Scientist, Sensor Technology

Google· Google Mountain View, Sensor Technology / Research
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Mountain View, CA, USA$207k - $300kFull-timePosted 3d ago

About the role

Senior Research Scientist position focusing on intersection of machine learning, signal processing, and embedded systems for future health and input technologies across Google’s consumer hardware portfolio. Leads multimodal foundation models for time-series sensor data, drives hardware-software co-design, and coordinates cross-functional teams to deploy AI-enabled edge features.

Responsibilities

  • Lead innovative research and development at the intersection of machine learning, signal processing, and embedded systems for future health and input technologies across Google’s consumer hardware portfolio.
  • Architect and train multimodal machine learning and foundation models tailored for time-series sensor data, while actively optimizing them for real-time inference on resource-constrained embedded systems.
  • Drive hardware-software co-design by partnering with Specialized Hardware Engineers, ensuring ML architectures and algorithmic requirements influence sensor definitions and edge-compute selection (e.g., MCUs, DSPs, micro-NPUs).
  • Define the long-term technical strategy spanning cloud-based ML training infrastructure down to on-device evaluation, guiding data collection pipelines and embedded software architecture.
  • Lead cross-functional integration efforts with Hardware, Firmware, Product, and Clinical teams to deploy optimized ML models and sensing algorithms into consumer-facing edge devices.

Qualifications

  • Minimum qualifications: - PhD in Computer Science, related field, or equivalent practical experience. - 4 years of experience in ML research, embedded signal processing, or applied algorithm development for consumer electronics, devices/services, or medical devices. - 3 years of experience in technical leadership, guiding research strategy, ML architecture, or algorithmic development for shipping products. - One or more scientific publication submissions (conferences, journals, or public repositories). Preferred qualifications: - 8 years of experience spanning ML research and embedded software engineering. - DSP experience and feature extraction from real-world noisy data. - Experience with ML frameworks (JAX, PyTorch, TensorFlow) and deploying models onto embedded/edge devices. - Experience building data pipelines and designing controlled ablations. - Expertise in edge AI and hardware/software co-design, model quantization, TinyML.

Skills

Required:Machine learning researchEmbedded systemsHardware-software co-design
Nice to have:Multimodal foundation modelsEdge AI

Benefits

  • Learn more about benefits at Google
Last updated Oct 23, 2026. Interested? Apply on the company site.

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