About the role
About Sesame 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 Vision understanding is a critical addition to conversational AI, bridging the gap between speech and the physical world. We’re looking for an engineer or researcher who lives at the intersection of 3D computer vision and machine learning. You’ll tackle problems ranging from gaze tracking to SLAM, embedding physical constraints (e..g. refraction, light transport) into data-driven models. Working cross-functionally with research, hardware, and product teams, you’ll turn cutting-edge vision techniques into features that power our next-generation wearables.
Responsibilities: Contribute to the development of our ML models across various flavors of 3D computer vision problems. Work across the ML stack, including model architectures, data capture, data curation, model evaluation, training & inference infrastructure, research, and experimentation. Collaborate with firmware and hardware engineers to deploy models onto embedded devices. Pick promising approaches from the literature to bet on, and create new approaches where necessary to achieve our unique goals. Required
Qualifications: Experience working with a high degree of autonomy in ambiguous environments. Proven experience in developing machine learning and computer vision models. Familiar with state-of-the-art in computer vision. Strong proficiency in deep learning frameworks such as PyTorch or Jax. Familiarity with large-scale dataset handling, including multi-camera datasets. Excellent communication skills and the ability to work collaboratively across disciplines. Bachelor’s degree or higher in computer science, computer vision, applied mathematics, machine learning, or a related field. Preferred