Sesame is looking to enable rich, reliable interactions on wearable devices by integrating embedded systems and ML.
Requirements
Proven experience building and deploying ML algorithms on embedded or resource-constrained devices.
Proficiency in Python and C/C++, with experience in frameworks such as PyTorch or TensorFlow.
Hands-on experience with end-to-end ML workflows, from data capture to on-device deployment.
Strong grasp of signal processing and/or time-series analysis for sensor data.
Experience with wearables, IMUs, or tactile/force sensors.
Familiarity with synthetic data generation and augmentation techniques.
Track record of optimizing algorithms for power, latency, and memory footprint.
Responsibilities
Design, train, and deploy algorithms for gesture detection on ultra-low-power embedded hardware.
Evaluate and adapt larger ML models for running on mobile class hardware.
Own the full development cycle: system design, data collection & curation, synthetic data generation, model training & evaluation, and on-device optimization.
Collaborate with electrical, mechanical, and product teams to integrate algorithms with evolving hardware designs.
Pick promising approaches from the literature to bet on, and create new approaches where necessary to achieve our unique goals.
Other
Experience working with a high degree of autonomy in ambiguous environments.
Excellent communication skills and the ability to work collaboratively across disciplines.
Bachelor’s degree or higher in computer science, electrical engineering, machine learning, or related field.
Master’s / Ph.D. in a relevant field.
Experience in a startup or fast-moving product environment.
