Sesame builds personal agents for curious people. Follow a thought. Work out an idea. Discover something new. Preview available now on iOS. Coming to intelligent eyewear in 2027. Backed by Sequoia and Redpoint.
About the role
New and novel approaches are needed to realize all of our product goals. As a Research engineer at Sesame, you are a research-oriented person with experience in NLP, Speech, and/or Computer Vision with a focus on deep learning. You are up to date on recent papers and approaches and you have the creativity and the intuition to come up with new solutions based on the application at hand.
What they're looking for
- Expert-level PyTorch
- Proven software engineer who loves ML, comfortable writing production code across the stack
- Hands-on experience training or fine-tuning large language or other large-scale models with a variety of techniques
- Evaluation expert — you’ve designed metrics and harnesses that actually predict user happiness
- Deep knowledge of the ML lifecycle: dataset ops, training pipelines, eval frameworks, deployment, and monitoring
- History of shipping complex projects to production—especially user-facing, online ML systems—despite shifting requirements and surprise roadblocks
More about this role
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.
New and novel approaches are needed to realize all of our product goals. As a Research engineer at Sesame, you are a research-oriented person with experience in NLP, Speech, and/or Computer Vision with a focus on deep learning. You are up to date on recent papers and approaches and you have the creativity and the intuition to come up with new solutions based on the application at hand.
Own evaluation pipelines — design, build, and automate offline and live evals that keep our speech and multimodal models honest in production.
Harness the data — create tooling for safe, versioned, privacy-aware dataset curation and discovery.
Ship models, not slide decks — partner with research and infra to...
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