23 hours ago
Sydney, AustraliaStaff+
Responsibilities
- Define and own the technical roadmap for ML infrastructure, including Kubernetes orchestration, distributed training, batch inference, real-time serving, and LLMOps.
- Lead and mentor a team of 3 to 4 mid-level and senior ML systems engineers and own technical hiring for the platform team.
- Design multi-cloud GPU capacity strategy and build foundational platform, observability, and reliability components.
- Write production Python and prototype new platform capabilities before implementation.
- Establish MLOps and AIOps practices covering automation, infrastructure as code, CI/CD, security, and the AI lifecycle.
- Partner with AI product teams to convert infrastructure challenges into an actionable platform roadmap.
- Own service-level objectives, GPU cost efficiency, major incident response, and detection of silent production ML failures.
Requirements
- 10+ years of software engineering experience, including at least 4 years building and operating large-scale infrastructure, platform engineering, or distributed systems in production.
- Experience leading technical projects and mentoring or managing engineering teams.
- Deep production expertise with Kubernetes, including GPU scheduling.
- Expert-level Python and strong distributed-systems judgment around failure, backpressure, and cost at scale.
- Hands-on experience managing AWS and GCP infrastructure with Terraform or Pulumi.
- Practical experience with Git, CI/CD, monitoring, alerting, and automated testing.
- Bachelor’s or Master’s degree in computer science, engineering, or a related technical field, or equivalent practical experience.
- Experience with workflow orchestration frameworks such as Argo Workflows, Kubeflow Pipelines, Flyte, Ray, or KubeRay is highly desirable.
- Experience with large-scale GPU-intensive ML workloads, multi-cloud GPU capacity strategy, MLOps and LLMOps ecosystems, model registries, feature stores, serving frameworks, vector databases, or RAG systems is highly desirable.
- Advanced Kubernetes experience with service mesh, custom operators, and multi-cluster networking, plus exposure to petabyte-scale data pipelines, geospatial or computer vision workloads, or relevant open-source projects, is highly desirable.
Benefits
- Remote and hybrid flexibility, including an approved Work from Overseas policy.
- Four additional “YOU” days off annually and quarterly wellbeing days.
- Company-sponsored volunteering days.
- Generous parental leave policies.
- Discounted private health insurance, wellbeing and technology allowance, and annual flu vaccinations.
- Nearmap subscription and stocked kitchen.
- In-office lunch every Tuesday and Thursday at the Sydney CBD office, with showers available for cyclists and gym-goers.
Tech Stack
Categories
About Nearmap
Nearmap provides high-resolution aerial imagery and AI-driven property intelligence delivered through web applications and APIs for insurers, government agencies, and AECO organizations. The company operates a recurring subscription model for frequently updated captures and analytics that support underwriting, claims, planning, and construction. Founded in 2009 and headquartered in Barangaroo, NSW, Nearmap was acquired by Thoma Bravo and serves customers across Australia, New Zealand, and North America.