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Sensing Systems Engineer

175k – 280kSan Francisco, CABellevue, WAEmbedded EngineeringOnsite5+ YOE
Summary

Owns end-to-end sensor system performance for consumer wearables, from hardware selection and integration through firmware, signal processing, and ML integration. Requires 5+ years in systems engineering with expertise in DSP, embedded systems, and shipping high-volume products.

About the role

Responsibilities

  • Sensing Architecture: Research, evaluate and recommend optimal sensor technologies and devices for various wearable applications, taking into account physical, electrical, and software capabilities along with cost, schedule, and user impact.
  • End-to-end Performance: Own the end-to-end performance of Sesame devices’ sensor systems from prototyping to mass production, including latency, power consumption, thermal constraints, and reliability.
  • System Requirements & Test: Champion a high quality user-experience by defining system-level test plans and acceptance criteria and detailed, actionable specifications for designing and validating each layer of the stack.
  • User data collection: Design and supervise a data collection strategy to gather ground-truth data sets necessary for algorithm and model development.
  • Algorithm Design: Develop, test, and implement the signal processing, sensor fusion and calibration systems that translate raw sensor data into usable outputs.
  • Model-sensor integration: Collaborate with Sesame’s ML team to determine how sensor data improves the quality of Sesame agents’ responses.

Required Qualifications

  • 5+ years of experience in systems engineering, sensor systems, algorithms and/or signal processing.
  • Demonstrated experience shipping high-volume consumer products from concept through production, in collaboration with electrical, firmware, and mechanical engineers.
  • Background in Sensor Physics: deeply understanding how sensor systems interact with the physical world, and how to design a test plan to isolate specific variables and behaviors in the system.
  • Understanding of electro-mechanical integration requirements and limitations of various sensors: Implementation constraints, best practices, areas for optimization.
  • Strong understanding of embedded systems: SoC architectures, memory management, wireless connectivity, power and thermal management, latency.
  • Proficiency in Digital Signal Processing (DSP) techniques: filtering, windowing, feature extraction, and sensor fusion.
  • Expert in Python for signal processing, data visualization, and algorithm development.
  • Excellent communication skills and ability to drive alignment across multiple engineering disciplines.
  • BS/MS in Electrical Engineering, Mechanical Engineering, Physics, or Computer Science (or equivalent experience).

Preferred Qualifications

  • Experience with wearable or small-form-factor consumer devices, especially on-device voice, audio, or camera processing pipelines.
  • Familiarity with AI/ML workloads on edge devices and their system-level implications (compute, memory, power).
  • Hands-on experience porting of algorithms and models to embedded systems, including experience with C/C++.
  • Multiphysics / FEA Experience: Proficiency with simulation tools (e.g., COMSOL, ANSYS) to model mechanical-electrical coupling and sensor response.
  • Experience with Machine Learning for signal processing.
  • Direct experience defining system architecture for a 0-to-1 product.
  • Experience in a startup or fast-moving, small-team product environment.

Benefits

  • 401(k) max employer match: 3.5% of compensation
  • 100% employer-paid health, vision, and dental benefits for you and your dependents
  • Unlimited PTO and sick time
  • Flexible spending account with employer matching up to $1,650/year (medical FSA)
  • Guardian Employee Assistance Program (EAP)
  • Opportunity to share in the company's success with competitive stock options
Skills
PythonDigital Signal ProcessingSensor FusionEmbedded SystemsC/C++COMSOLANSYSMachine LearningSignal ProcessingSoC Architectures
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