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Lead Platform / DevOps / MLOps Engineer
Build the platforms that enable AI to run in the real world
We’re hiring a Lead Platform / DevOps / MLOps Engineer to design and operate a Kubernetes-based MLOps platform powering production AI and LLM workloads.
This is a hands-on technical leadership role — not people management. You’ll sit at the intersection of platform engineering and machine learning, enabling teams to deliver AI safely and at scale.
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🔍 Why this role?
You won’t just run Kubernetes — you’ll turn it into a usable ML platform.
This is about real production impact, not experimentation in isolation.
⚙️ What you’ll do
- Build and operate MLOps platforms on Kubernetes
- Enable model training, deployment, and scalable inference
- Implement tooling (e.g. Kubeflow, KServe, LLM serving stacks)
- Support data scientists in real production workflows
- Own reliability, security, and operability of the platform
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✅ What you’ll bring
- Strong Platform / DevOps engineering background
- Deep Kubernetes + Terraform + Helm experience
- Proven experience building usable internal platforms
- Exposure to MLOps, model serving, or LLM workloads
- Pragmatic mindset focused on usability and outcomes
👉 If you enjoy building platforms that engineers actually want to use — and enabling AI at scale — apply now.
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