About IRL (Instawork Robotics Labs) Researchers at UC Berkeley have identified a “100,000-year data gap”—the gulf between what trained AI language models and what physical robots actually have to learn from. Closing that gap is the defining infrastructure challenge of the physical AI era. IRL is Instawork’s answer to it. We deploy skilled workers into real commercial and residential environments—kitchens, warehouses, hotel floors, and homes—to capture the high-fidelity task data that the world’s leading robotics labs use to train their foundation models. About the Role Instawork Robotics creates the highest-quality, highest-diversity datasets for robotics and physical AI. We work with leading robotics builders and research labs to solve one of the most important challenges in robotics: closing the data gap. As a Platform Engineer, you will build the products, services, tools, and infrastructure that power IRL’s data collection, processing, and quality workflows. This is a hybrid product and infrastructure role: you will design platform capabilities for application engineers while also owning the reliability, scalability, cost efficiency, and operation of the systems behind them.

You will collaborate across Engineering, Operations, and Business teams to translate customer requirements into clear, scalable technical solutions, leveraging AI methodologies to deliver high-quality products and efficient software workflows. You’ll work across distributed systems, Kubernetes, cloud infrastructure, observability, and high-throughput data workflows—supporting a platform already processing 50+ PB of data and 600K+ hours of video.

You are someone who thrives in ambiguous problem spaces, has strong product instincts, and can translate customer needs into technical solutions that drive business outcomes.

Who You Are - 5+ years of experience building and operating production software platforms. - Experience designing platform products, backend services, developer tools, or internal systems. - Proven experience managing Kubernetes clusters at scale in production. - Strong understanding of distributed systems, cloud infrastructure, networking, storage, and observability. - Experience with Infrastructure as Code, CI/CD, and production operations. - Strong programming and problem-solving skills. - Experience with Python and Rust is preferred. - Experience with AWS and Azure is preferred. - Experience operating multi-cloud deployments is preferred. - Experience with managed Kubernetes services such as Amazon EKS or Azure AKS is preferred. - Experience designing cost-efficient cloud and platform architectures. - Understanding of cloud cost management, capacity planning, resource utilization, and usage optimization. What You’ll Do - Design and build platform products, backend services, APIs, tools, and workflows used by application engineers. - Manage, scale, and improve Kubernetes clusters supporting production workloads. - Design and maintain reliable cloud infrastructure across AWS, Azure, and other cloud platforms. - Build automation for infrastructure provisioning, deployments, upgrades, and operational workflows. - Develop platform capabilities using Python, Rust, or other appropriate technologies. - Improve observability through monitoring, logging, alerting, tracing, and capacity management. - Define and improve service-level objectives, incident response processes, and recovery procedures. - Monitor and optimize infrastructure costs across cloud services, Kubernetes workloads, and platform systems. - Improve resource utilization through right-sizing, autoscaling, capacity planning, and cost-aware architecture decisions. - Troubleshoot complex issues across platform services, Kubernetes, cloud infrastructure, networking, storage, and applications. - Participate in an on-call rotation and take ownership of diagnosing and resolving production issues. - Support the infrastructure and product needs of high-throughput data and physical AI workflows. - Participate in code reviews and raise the technical bar through clear, practical feedback. - Own complex platform initiatives from problem definition through design, implementation, and operation. - Measure and improve platform adoption, deployment lead time, reliability, incident recovery time, resource utilization, and infrastructure cost per workload. Perks - Free snacks - Health Insurance - Personal Insurance - Flexible Hours - Maternity/Paternity Leave - Broadband Reimbursement