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Sesame · Hiring

Data Engineer, Machine Learning

San FranciscoOn SiteFull Time$170K – $240K

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

We're looking for a Data Engineer to build and maintain the data pipelines that feed Sesame's AI models. You'll collaborate directly with machine learning engineers and researchers — your job is to make sure they have the right data, in the right shape, at the right time to train, evaluate, and ship models.

Sesame's data is rich and complex: conversations, voice, sensor signals, and product telemetry. You'll design the systems that take raw, unstructured, multimodal data and turn it into clean, versioned, well-documented datasets that ML teams can trust and build on confidently.

This is a deeply technical, infrastructure-focused role — closer to ML engineering than traditional data analytics. You'll be deeply embedded with ML teams, understanding their workflows and building infrastructure that accelerates the full model development lifecycle — from data collection and labeling through training and evaluation.

Responsibilities

Required Qualifications:

Preferred Qualifications:

Sesame is committed to a workplace where everyone feels valued, respected, and empowered. We welcome all qualified applicants, embracing diversity in race, gender, identity, orientation, ability, and more. We provide reasonable accommodations for applicants with disabilities. Contact careers@sesame.com for assistance.

Full-time Employee Benefits: 

Benefits do not apply to contingent/contract workers.

Interested in This Role?

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