Job description

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. RESPONSIBILITIES: - Design, build, and maintain secure, maintainable, self-serve core infrastructure that engineering teams can rely on and operate independently. - Lead the architecture and evolution of a modern ML training infrastructure — scalable, reproducible, and built for rapid experimentation. - Build and operate a modern model serving architecture with a focus on reliability, cost efficiency, and low latency. - Lead and own the low-latency voice interface and audio processing pipeline — a technically demanding, performance-sensitive system at the core of Sesame's product. - Build developer tooling, server infrastructure, and data infrastructure that is high leverage and low maintenance — the kind that makes other engineers faster without creating new dependencies on you. - Lead technical direction within your domain, bring others along through clear communication and well-reasoned proposals, and raise the engineering bar across the team. REQUIRED QUALIFICATIONS: - A strong systems thinker who is equally comfortable leading technical direction and getting hands-on with implementation. - 7+ years of software engineering experience, with significant time in infrastructure, platform, or ML systems roles. - Hands-on reliability engineering experience — you have well-formed convictions about observability, monitoring, deployment systems, and loosely coupled architectures, and you've put them into practice at scale. - Proven track record of building and shipping services at scale, with all the operational complexity that comes with it. - Kubernetes — significant production experience building, operating, and scaling Kubernetes clusters. - Experience designing and shipping flexible domain models and APIs — you think carefully about boundaries, contracts, and long-term maintainability. - A default toward automation — you've consistently built efficiency gains through automation and have the track record to show it. - Strong communication skills — you can lead your own direction, write clearly about tradeoffs, and bring engineers and stakeholders along with you. PREFERRED QUALIFICATIONS: We'd love to hear about experience in any of these areas — we don't expect any one person to have all of them: - Infrastructure as Code at scale — significant IaC experience, preferably Terraform; CloudFormation, Pulumi, or Kubernetes-based approaches also welcome. Ideally you've led, architected, or contributed to a multi-stack, self-serve IaC system and understand the challenges of building infra that teams can own independently. - ML infrastructure — any combination of the following: - PyTorch experience, especially model optimization for serving. - ML training or serving experience in general. - Experience building ML serving and/or training infrastructure (TorchServe, Seldon, KServe, Ray Serve, or similar). - Experience building and leading large-scale distributed training and serving systems. - Data engineering — pipeline design, dataset management, or data platform experience. - Database design — complex schema design, query optimization, and hard data modeling decisions across relational and non-relational stores. - Real-time communication systems — low-latency audio, video, or streaming infrastructure. 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: - 401 (k) max employer match: 3.5% of compensation - 100% employer-paid health, vision, and dental benefits for you and your dependents - Unlimited PTO and sick time - Flexible spending account with employer matching up to $1,650/year (medical FSA) - Guardian Employee Assistance Program (EAP) - Opportunity to share in the company's success with competitive stock options Benefits do not apply to contingent/contract workers.

Requirements

Must-haves

Design, build, and maintain secure, maintainable, self-serve core infrastructure that engineering teams can rely on and operate independently.
Lead the architecture and evolution of a modern ML training infrastructure — scalable, reproducible, and built for rapid experimentation.
Build and operate a modern model serving architecture with a focus on reliability, cost efficiency, and low latency.
Lead and own the low-latency voice interface and audio processing pipeline — a technically demanding, performance-sensitive system at the core of Sesame's product.
Build developer tooling, server infrastructure, and data infrastructure that is high leverage and low maintenance — the kind that makes other engineers faster without creating new dependencies on you.
Lead technical direction within your domain, bring others along through clear communication and well-reasoned proposals, and raise the engineering bar across the team.
A strong systems thinker who is equally comfortable leading technical direction and getting hands-on with implementation.
7+ years of software engineering experience, with significant time in infrastructure, platform, or ML systems roles.
Hands-on reliability engineering experience — you have well-formed convictions about observability, monitoring, deployment systems, and loosely coupled architectures, and you've put them into practice at scale.
Proven track record of building and shipping services at scale, with all the operational complexity that comes with it.
Kubernetes — significant production experience building, operating, and scaling Kubernetes clusters.
Experience designing and shipping flexible domain models and APIs — you think carefully about boundaries, contracts, and long-term maintainability.
A default toward automation — you've consistently built efficiency gains through automation and have the track record to show it.
Strong communication skills — you can lead your own direction, write clearly about tradeoffs, and bring engineers and stakeholders along with you.
401 (k) max employer match: 3.5% of compensation

Nice-to-haves

We'd love to hear about experience in any of these areas — we don't expect any one person to have all of them:
ML infrastructure — any combination of the following:
PyTorch experience, especially model optimization for serving.
ML training or serving experience in general.
Experience building ML serving and/or training infrastructure (TorchServe, Seldon, KServe, Ray Serve, or similar).
Experience building and leading large-scale distributed training and serving systems.
Data engineering — pipeline design, dataset management, or data platform experience.
Database design — complex schema design, query optimization, and hard data modeling decisions across relational and non-relational stores.
Real-time communication systems — low-latency audio, video, or streaming infrastructure.

Application prep

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Keywords to mirror

mlkubernetes

Platform: ashby
Effort: quick

Benefits

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Dental

Vision

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