
51 - 200 employees
🤖 Artificial Intelligence
🔌 API
🚘 Automotive
💰 $30M Series B on 2022-11
Artificial Intelligence • API • Automotive
Parallel Domain is a company that offers an API for machine learning, computer vision, and perception teams to generate high-fidelity synthetic sensor data, including camera, lidar, and radar data. This data helps in training and testing perception models by simulating scenarios in procedurally generated worlds or replicas of any real-world location. The platform provides high-quality synthetic data to analyze, train, evaluate, and monitor perception models, enhancing AI reliability while reducing risks, development time, and costs. Parallel Domain supports various perception use cases across multiple industries, such as automotive and drones, by offering diverse datasets with edge cases and accurate annotations, thereby boosting machine learning model performance for tasks like emergency vehicle detection and traffic light classification systems.
🕒 April 28
🌐 Canada, United States – Remote
💵 $145k - $185k / year
⏰ Full Time
🟠 Senior
⛑ DevOps & Site Reliability Engineer (SRE)
👻 Ghost score 42%
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51 - 200 employees
🤖 Artificial Intelligence
🔌 API
🚘 Automotive
💰 $30M Series B on 2022-11
Artificial Intelligence • API • Automotive
Parallel Domain is a company that offers an API for machine learning, computer vision, and perception teams to generate high-fidelity synthetic sensor data, including camera, lidar, and radar data. This data helps in training and testing perception models by simulating scenarios in procedurally generated worlds or replicas of any real-world location. The platform provides high-quality synthetic data to analyze, train, evaluate, and monitor perception models, enhancing AI reliability while reducing risks, development time, and costs. Parallel Domain supports various perception use cases across multiple industries, such as automotive and drones, by offering diverse datasets with edge cases and accurate annotations, thereby boosting machine learning model performance for tasks like emergency vehicle detection and traffic light classification systems.
• Design, build, and maintain multi-region AWS infrastructure using Terraform • Operate and scale EKS clusters across production regions, including autoscaling, node lifecycle, and workload health • Manage VPC design, DNS, load balancing, and cross-region connectivity • Support infrastructure changes, migrations, and expansions into new regions • Improve GitOps deployment workflows using GitHub Actions, Helm, and Kustomize • Build and run incident management processes, including severity definitions, escalation paths, and on-call practices • Lead incident response, debugging, and root-cause analysis • Write postmortems and drive systemic reliability improvements • Improve observability across metrics, logging, tracing, and dashboards • Support GPU and batch workloads running on Kubernetes • Provide security-conscious feedback on platform architecture • Own cloud IAM governance across accounts and services • Lead audit-readiness, partner certification, and customer security questionnaire support • Improve CI/CD pipelines and infrastructure validation • Support engineers with infrastructure debugging, environment setup, and performance issues • Contribute to Python and Bash tooling and automation • Partner with platform, simulation, and ML teams to operate large-scale distributed simulation infrastructure
• 5+ years in SRE, DevOps, or infrastructure engineering roles • Track record of operating production systems across multiple regions • Experience with Terraform modules, state management, and multi-environment patterns • Solid experience across AWS VPC, IAM, EKS, S3, and CloudWatch • Kubernetes expertise including cluster operations, autoscaling, RBAC, and Helm • Experience with GitHub Actions, ArgoCD, or similar CI/CD and GitOps workflows • Networking knowledge including CIDR, DNS, load balancing, VPN, and cross-region connectivity • Experience with observability tools such as Prometheus and Grafana • Python and Bash scripting for tooling and automation • Working knowledge of Linux and Windows environments • Comfortable in a fast-moving startup with evolving priorities • Preferred: Windows node pools, Windows AMIs, GPU-adjacent Kubernetes components • Preferred: GPU scheduling on Kubernetes, including NVIDIA device plugin configuration • Preferred: simulation, ML, or rendering workloads in cloud infrastructure • Preferred: AWS Storage Gateway, Active Directory integrations, or AWS Transfer Family • Preferred: service proxy or service mesh patterns • Preferred: container-optimized OS images such as Bottlerocket or Packer • Preferred: cloud cost optimization at scale
• Equity • Full health/dental/vision coverage • Learning stipend • Generous vacation • Remote-friendly work across Canada and the US Pacific Northwest
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