Associate, Kubernetes Engineer

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New York / $150000 - $180000 annum

INFO

Salary

SALARY:

$150000 - $180000

Location

LOCATION

New York

Job Type
JOB TYPE

Permanent

Associate Kubernetes Engineer (AI / Machine Learning Infrastructure)

A globally recognized enterprise technology organization is hiring an Associate-level Kubernetes Engineer to join a highly strategic Machine Learning Platform Engineering team responsible for building and scaling the cloud-native infrastructure powering AI and machine learning systems across the company.

This team sits at the intersection of Kubernetes, cloud infrastructure, GPU-accelerated computing, distributed systems, and machine learning platform engineering, supporting internal data science and engineering teams building next-generation AI systems at enterprise scale.

Why This Opportunity Stands Out

The organization is making a significant long-term investment in modernizing its firm-wide AI and machine learning infrastructure, transitioning from legacy hybrid environments into fully cloud-native, Kubernetes-based platforms optimized for GPU-enabled AI workloads and large-scale model deployment.

This is an opportunity to work on infrastructure supporting the entire machine learning lifecycle - from model training and experimentation through inference and production deployment - while learning directly from a highly senior engineering team operating at exceptional scale.

Key Responsibilities

  • Deploy and operate production-grade Kubernetes clusters supporting machine learning workloads
  • Support internal ML engineers by maintaining infrastructure for model training, experimentation, deployment, and real-time inference
  • Build and maintain GPU-enabled infrastructure environments supporting AI workloads
  • Deploy and integrate machine learning tooling including Kubeflow, notebook environments, inference services, and model runtime infrastructure
  • Work with cloud-native infrastructure as the organization migrates fully toward Google Kubernetes Engine (GKE)
  • Support deployment and operationalization of Large Language Models (LLMs) for internal enterprise use cases
  • Improve platform reliability, scalability, observability, and system performance across distributed environments

Required Experience

  • Strong hands-on experience with Kubernetes (deploying workloads, not simply cluster administration)
  • Experience supporting machine learning infrastructure or ML tooling on Kubernetes
  • Understanding of the machine learning development lifecycle (training, experimentation, deployment, inference)
  • Programming experience with Python or Go
  • Experience working with cloud-native infrastructure environments
  • Strong understanding of distributed systems and infrastructure reliability

Preferred Experience

  • GPU workload deployment
  • NVIDIA operator experience
  • Kubeflow or notebook environments
  • Kubernetes controllers / CRDs
  • Google Kubernetes Engine (GKE)
  • Exposure to production AI or LLM deployment infrastructure

Compensation & Location

  • Compensation highly competitive with strong bonus structure
  • Locations: New York / New Jersey, Toronto, or Dallas
  • Primarily onsite environment with some team-level flexibility
  • Visa sponsorship available

This is an exceptional opportunity for engineers looking to deepen expertise at the intersection of Kubernetes, AI infrastructure, cloud-native systems, and next-generation machine learning platforms operating at enterprise scale.

CONTACT

Tim Greenwald

Senior Recruitment Consultant

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