Job Opportunities API

By combining proprietary motion capture data with state-of-the-art diffusion models, we enable game studios to generate dynamic, lifelike motion in minutes instead of weeks, removing one of the biggest bottlenecks in game and cinematic production. We are scaling rapidly due to early demand from major game studios and are at a breakthrough moment. The Role We are looking for a Platform Engineer - our first - to build the foundation of Motorica's internal developer platform. You'll define the “paved road” for developer experience while keeping our systems secure, compliant, and cost-efficient. It's a hands-on role with a lot of ownership: you set the technical direction, but you also do the work. Our infrastructure spans a multi-cloud environment managed entirely through Infrastructure as Code, covering GPU-accelerated ML serving, event-driven pipelines, API gateways, managed databases, self-hosted CI/CD runners, compliance tooling, and multi-environment deployments. We operate at the intersection of platform engineering and ML infrastructure, and we need someone with deep expertise to drive this forward. Who you are You’re comfortable being the only person who owns a domain, you’re biased toward shipping over perfecting, calm under incidents, treats developer experience as a product with internal customers, opinionated but not precious about being overruled. What You'll Own: • Infrastructure as Code: Design, build, and maintain reusable IaC modules across a multi-cloud environment. Manage multi-environment deployments with proper state management, versioning, and security boundaries. • CI/CD & Developer Experience: Own our deployment pipelines and monorepo build system. Streamline the path from code to production and improve developer self-service. • ML Infrastructure & GPU Workloads: Maintain and scale our GPU-accelerated ML serving layer, experiment tracking, and ML job orchestration on Kubernetes. • Cloud Platform & Networking: Manage API gateways, load balancers, DNS, VPC networking, and our multi-cloud footprint including IAM and credential federation. • Security & Compliance: Own our security posture: compliance tooling, threat detection, audit trails, least-privilege IAM, and secrets management across all environments. • Reliability & Observability: Own monitoring, alerting, SLOs/SLIs, incident response tooling, and status page infrastructure. • Cost Management: Optimize cloud spend across GPU workloads, Kubernetes clusters, storage, and compute. Maintain budget monitoring and alerting. A Typical Week • Manage CI/CD systems (GitHub Actions, GitLab CI) and track build times, deployment frequency, and failure rates. • Oversee cloud environments (AWS, GCP) - health, security, and cost reporting. • Lead security scans, audits, and vulnerability remediation. • Maintain the observability stack (Prometheus, Grafana, Datadog, GCP Logging) with meaningful dashboards and alerts. • Act as point of contact for the ML Research team's infra requests (GPU access, specialized pipelines). • Be the first line of support for developer infrastructure issues, and own the platform roadmap. What We're Looking For Must Have • Proven experience in Platform Engineering, SRE, or DevOps - ideally in a high-growth or AI/ML-heavy environment. • Deep cloud infrastructure expertise across at least one major cloud provider, with working knowledge of a second. Experience with managed compute, serverless, managed databases, messaging, IAM, networking, secrets management, and monitoring. • Strong IaC skills — you've designed module libraries, managed multi-environment state, and understand the difference between good and great infrastructure code. Experience with Terraform or OpenTofu. • Kubernetes experience - you've operated clusters in production, managed Helm deployments, and understand node pool autoscaling, wor