Principal AI Platform Engineer

Nearmap provides aerial imagery, AI-driven analytics, and geospatial tools for understanding the built environment. The Principal AI Platform Engineer will architect and own the platform powering AI innovation, lead a team of ML systems engineers, define the ML infrastructure roadmap, and drive scalable, efficient MLOps and AIOps across AWS and GCP.

Responsibilities:

• Define and own the technical roadmap for core ML infrastructure: workflow orchestration on Kubernetes, distributed training, batch inference at thousands-of-nodes scale, real-time serving on Ray, and LLMOps
• Make the critical design calls and evaluate new technologies, from orchestrators and serving frameworks to vector databases
• Lead and mentor a team of 3 to 4 mid-level and senior ML systems engineers, and own technical hiring for the platform team
• Spearhead the highest-risk work yourself: multi-cloud GPU capacity strategy, foundational platform components, and the observability stack
• Write production Python for the hardest parts of the shared platform, and prototype new capabilities before the team commits to them
• Establish and champion MLOps and AIOps best practice across the organisation, covering automation, infrastructure as code, CI/CD, and security through the AI lifecycle
• Partner with Data Science and ML Engineering teams, turning their challenges into an actionable platform roadmap
• Own service level objectives and GPU cost efficiency across AWS and GCP, lead major incident response, and build detection for the ways production ML fails quietly