SWE - Backend Infrastructure Engineer

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
• 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

• Infrastructure as Code at scale — significant IaC experience, preferably Terraform; CloudFormation, Pulumi, or Kubernetes-based approaches also welcome
• ML infrastructure — PyTorch experience, especially model optimization for serving; ML training or serving experience; building ML serving and/or training infrastructure (TorchServe, Seldon, KServe, Ray Serve); 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

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