Sensing Systems Engineer

Sesame•San Francisco, CA

17h

About The Position

Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human. With this vision, we're designing a new kind of computer, focused on making voice agents part of our daily lives. Our team brings together founders from Oculus and Ubiquity6, alongside proven leaders from Meta, Google, and Apple, with deep expertise spanning hardware and software. Join us in shaping a future where computers truly come alive. About the role Sesame is developing new consumer wearables whose purpose is to enrich the human-computer interface with novel interaction modes, including the use of new and available sensor systems. We are looking for a Systems Engineer to own the holistic performance of Sesame’s devices across the full stack—from hardware selection and integration through firmware, signal processing, and application behavior. The ideal candidate thrives in crossing the boundaries between disciplines to ensure product-level goals are translated into technical requirements that deliver a magical experience in users' hands. You'll be the connective tissue between hardware, firmware, application, ML, and product teams, ensuring every layer works in concert from proof of concept prototypes to shipping in mass production.

Requirements

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).

Nice To Haves

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.

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.