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Senior Software Engineer (Simulation Orchestration) at Applied Intuition · Katori

Asks for

The ad says“Deep Kubernetes expertise, including pod scheduling, node lifecycle, and autoscaling under load”
The ad says“Multi-cloud (AWS, OCI, GCP, Azure) or on-prem Kubernetes deployments”
The ad says“Multi-cloud (AWS, OCI, GCP, Azure) or on-prem Kubernetes deployments”
The ad says“4+ years of coding in Golang, Python, Java, or C++”
The ad says“Experience with cloud cost optimization strategies for high-scale compute workloads”
The ad says“4+ years building complex backend systems on major cloud providers”
The ad says“Multi-cloud (AWS, OCI, GCP, Azure) or on-prem Kubernetes deployments”
The ad says“4+ years of coding in Golang, Python, Java, or C++”
The ad says“Experience scheduling GPU workloads or managing GPU capacity at scale”
The ad says“Experience managing multi-cluster environments using Infrastructure as Code”
The ad says“4+ years of coding in Golang, Python, Java, or C++”
The ad says“Deep Kubernetes expertise, including pod scheduling, node lifecycle, and autoscaling under load”
The ad says“Experience building custom Kubernetes controllers or operators”
The ad says“Multi-cloud (AWS, OCI, GCP, Azure) or on-prem Kubernetes deployments”
The ad says“Experience building custom Kubernetes controllers or operators”
The ad says“Deep Kubernetes expertise, including pod scheduling, node lifecycle, and autoscaling under load”
The ad says“Multi-cloud (AWS, OCI, GCP, Azure) or on-prem Kubernetes deployments”
The ad says“Deep Kubernetes expertise, including pod scheduling, node lifecycle, and autoscaling under load”
The ad says“4+ years of coding in Golang, Python, Java, or C++”
The ad says“Experience building or operating workload scheduling systems (e.g., dispatch, bin-packing, quota enforcement)”

As a senior software engineer on the Simulation Orchestration team, you will own the compute platform that Applied Intuition’s autonomy products run on. Our customers, and our own internal self-driving programs, run millions of simulations to validate every change to their self-driving stack — throughput is directly how fast they ship
From that foundation, the team is expanding to own on-demand compute scheduling and capacity management across Applied: one platform, any workload, any environment
Develop a multi-environment compute platform for workload scheduling, resource allocation, and node lifecycle
Collaborate with customers and internal teams to translate compute needs into platform features
Solve distributed systems challenges including GPU scheduling, autoscaling, and resource efficiency
Ensure high reliability and scalability for production simulation systems
Drive architecture decisions to expand simulation orchestration into a company-wide compute platform

Preferred experience

4+ years of coding in Golang, Python, Java, or C++
Deep Kubernetes expertise, including pod scheduling, node lifecycle, and autoscaling under load
Experience building or operating workload scheduling systems (e.g., dispatch, bin-packing, quota enforcement)
Self-starter with experience driving production system development from 0 to 1
4+ years building complex backend systems on major cloud providers
5+ years of backend engineering experience, with a track record of owning production distributed systems
Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles
Experience with cloud cost optimization strategies for high-scale compute workloads
Experience managing multi-cluster environments using Infrastructure as Code
Multi-cloud (AWS, OCI, GCP, Azure) or on-prem Kubernetes deployments
Experience scheduling GPU workloads or managing GPU capacity at scale
Experience building custom Kubernetes controllers or operators