SWE - Backend Infrastructure Engineer

Sesame
Bellevue, US
On-site

Who this role is best for

Geared toward senior infrastructure engineers comfortable with architecting ML training and serving systems while scaling Kubernetes clusters in a real-time audio processing environment.

Best fit for

  • Senior engineers who automate infrastructure at scale with Kubernetes and IaC.
    — “significant production experience operating and scaling Kubernetes clusters
  • Systems thinkers who balance architecture with hands-on implementation of ML infrastructure.
    — “A strong systems thinker who is equally comfortable setting direction and getting hands-on with implementation
  • Engineers experienced in low-latency real-time communication systems like audio processing.
    — “low-latency voice interface and audio processing pipeline

Things to consider

  • Involves building ML infrastructure, not just consuming existing frameworks.
    — “Architect and evolve a modern ML training infrastructure

How to stand out

  • Highlight specific efficiency gains achieved through automation in past roles.
    — “delivered efficiency gains through automation and have the track record to show it
  • Showcase experience designing APIs with long-term maintainability in mind.
    — “think carefully about boundaries, contracts, and long-term maintainability
  • Demonstrate contributions to self-serve infrastructure that reduced team dependencies.
    — “infra that teams can own independently
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Designed and built secure, maintainable, self-serve core infrastructure
  • Built and operated a modern model serving architecture
Typical background
3+ years of software engineering experience in infrastructure, platform, or ML systems roles

Skills & requirements

Required

Reliability EngineeringKubernetesML InfrastructureData Infrastructure

Preferred

Infrastructure As CodeML Training And Serving Infrastructure

Stack & domain

KubernetesTerraformPyTorchMl InfrastructureData EngineeringCommunicationBackend InfrastructureMl TrainingModel Serving

About the role

As a Backend Infrastructure Engineer at Sesame, you'll be crafting the backbone of a lifelike computing experience, working closely with a team of experts to design and implement robust, scalable systems that enable seamless voice interactions and support rapid experimentation in machine learning.

Original posting from Sesame via Ashby

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 and build secure, maintainable, self-serve core infrastructure that engineering teams can rely on and operate independently
  • Architect and evolve 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
  • Own and scale 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
  • Set 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 setting direction and getting hands-on with implementation
  • 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 shipping services at scale, with all the operational complexity that comes with it
  • Kubernetes — significant production experience 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 delivered efficiency gains through automation and have the track record to show it
  • Strong communication skills — you can set your own direction, write clearly about tradeoffs, and bring engineers and stakeholders along with you
  • 3+ years of software engineering experience, with significant time in infrastructure, platform, or ML systems roles

PREFERRED QUALIFICATIONS

We'd love to hear about experience in most 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 architected, maintained, 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 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.

Source: Sesame careers (Ashby)

Similar roles