Develop Kubernetes Custom Resource Definitions, Operators, and Controllers in Golang to orchestrate AI workloads.

Build GPU-aware scheduling, resource isolation, and workload orchestration capabilities for AI infrastructure.

Drive architectural reviews, establish coding standards, and mentor junior and mid-level engineers.

Design and scale distributed systems, global control-plane and cell-based architectures, and resilient platform infrastructure.

Partner with Product Managers, the core Kubernetes team, and Nutanix Data Services on data gravity and persistent storage for AI workloads.

6–8 years of software engineering experience, including at least 3 years building scalable distributed systems, cloud platforms, or AI/ML infrastructure.

- Deep expertise in Golang and Python.
- Hands-on experience with MLOps frameworks and distributed AI computing, such as Kubeflow, Ray, KServe, and PyTorch DDP.
- Strong understanding of Linux internals, networking, and container runtimes including containerd and Docker.




- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
- Preferred qualifications include contributions to CNCF or AI open-source projects, familiarity with Milvus, Qdrant, or PGVector and RAG architectures, and experience with Prometheus, Grafana, or OpenTelemetry for AI observability metrics.

Dedicated mental health coverage and paramedical perks.

Fully paid maternity and parental leave plus bereavement leave.

Company holidays, sick days, wellness days, and vacation starting at 10 days.

Hybrid work arrangement in Vancouver and other applicable locations, with employees expected to work onsite at least 3 days per week where the workplace policy applies.

The role requires no travel.

Nutanix does not assist with applications for work permits or permanent residence, including provincial nomination.

📌 Software Development Engineer - Machine Learning (Vancouver)
🏢 Nutanix
📍 Vancouver