Senior Member of Technical Staff
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Key skills for this role
About the Role
Nutanix is seeking a Senior Engineer to join the NKP AI Platform team, architecting and scaling infrastructure for enterprise AI/ML workloads on Kubernetes. You will develop CRDs, Operators, and Controllers in Golang, integrate open-source AI tools, and mentor junior engineers.
Key Skills for This Role
Responsibilities
- Develop Kubernetes Custom Resource Definitions (CRDs), Operators, and Controllers in Golang to natively orchestrate AI workloads.
- Build scheduling intelligence for AI native infrastructure, including GPU aware scheduling, resource isolation, and workload orchestration.
- Seamlessly integrate and manage the lifecycle of leading open source AI tools like Kubeflow, KServe, Ray, vLLM, and Triton Inference Server within the NKP stack.
- Drive architectural reviews, establish coding standards, and mentor junior and mid level engineers to act as a technical force multiplier.
- Partner closely with Product Managers, the core NKP K8s team, and Nutanix Data Services (NDK) to ensure seamless data gravity and persistent storage for AI workloads.
Requirements
- 8+ years of software engineering experience
- 3+ years focused on building scalable distributed systems, cloud platforms, or AI/ML infrastructure
- Deep expertise in Golang (for K8s ecosystem) and Python (for ML ecosystem)
- Extensive experience with Kubernetes internals, building K8s Operators, Controllers, and working with Cluster API (CAPI)
- Hands on experience with MLOps frameworks and distributed AI computing (e.g., Kubeflow, Ray, KServe, PyTorch DDP)
- Strong understanding of Linux internals, networking, and container runtimes (containerd, Docker)
- Proven track record of designing intuitive, developer friendly APIs and scalable microservices architectures
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field (or equivalent practical experience)
Full Job Posting
The Opportunity
- At Nutanix, we are expanding the capabilities of the Nutanix Kubernetes Platform (NKP) to power the next generation of enterprise AI.
- This platform serves as the foundation for AI/ML workloads, GPU infrastructure, and enterprise applications, delivering hyperscaler like capabilities across on prem and hybrid deployments.
- As a Senior Engineer on the NKP AI Platform team, you will be a key technical leader responsible for architecting, building, and scaling the infrastructure that allows enterprises to train, deploy, and manage mission critical modern and AI Applications effortlessly.
About the Team
- NKP is a complete, enterprise grade, production ready platform based on Kubernetes that serves modern applications.
- You will report to the Senior Engineering Manager, who adopts a collaborative leadership style that encourages team involvement in decision making and values open discussions.
- This role does not require any travel.
Your Role
- Develop Kubernetes Custom Resource Definitions (CRDs), Operators, and Controllers in Golang to natively orchestrate AI workloads.
- Build scheduling intelligence for AI native infrastructure, including GPU aware scheduling, resource isolation, and workload orchestration.
- Seamlessly integrate and manage the lifecycle of leading open source AI tools like Kubeflow, KServe, Ray, vLLM, and Triton Inference Server within the NKP stack.
- Drive architectural reviews, establish coding standards, and mentor junior and mid level engineers to act as a technical force multiplier.
- Partner closely with Product Managers, the core NKP K8s team, and Nutanix Data Services (NDK) to ensure seamless data gravity and persistent storage for AI workloads.
What You Will Bring
- 8+ years of software engineering experience, with at least 3+ years focused on building scalable distributed systems, cloud platforms, or AI/ML infrastructure.
- Deep expertise in Golang (for K8s ecosystem) and Python (for ML ecosystem).
- Extensive experience with Kubernetes internals, building K8s Operators, Controllers, and working with the Cluster API (CAPI).
- Hands on experience with MLOps frameworks and distributed AI computing (e.g., Kubeflow, Ray, KServe, PyTorch DDP).
- Strong understanding of Linux internals, networking, and container runtimes (containerd, Docker).
- Proven track record of designing intuitive, developer friendly APIs and scalable microservices architectures.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field (or equivalent practical experience).
Highlighted Benefits (Vancouver, Canada)
- Retirement: RRSP with dollar for dollar matching up to 7% of base salary
- Mental Health: Dedicated mental health coverage plus top tier paramedical benefits
- Family: Fully paid maternity and parental leave and generous bereavement leave, including time for the loss of a pet
- Equity: RSUs and Employee Stock Purchase Plan at a 15% discount
- Time Off: Company holidays, sick days, company wellness days, and vacation starting at 10 days
Work Arrangement
- Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in person collaboration.
- Employees are expected to work onsite a minimum of 3 days per week to foster collaboration, team alignment, and access to in office resources.
Pay Transparency
- The pay range for this position at commencement of employment is expected to be between CAD 171,200 and CAD 256,800 per annual.
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