Job Description

Machine Learning Engineer

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This range is provided by NineTech. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

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Base pay range

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A$90.00/hr - A$90.00/hr

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Direct message the job poster from NineTech

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We're urgently seeking a Senior DevOps ML Engineer with a rare combination of DevOps leadership, software engineering depth, and MLOps expertise.

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The client requires someone with DevOps leadership, coding skills akin to a seasoned backend engineer, and ability to optimize AI systems with precision.

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You will be responsible for the end-to-end design, deployment, and operation of AI platforms.

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Expect to split your time approximately as follows: 60% DevOps/AI infrastructure, 30% backend coding, and 10% MLOps/model lifecycle tasks.

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One week, you may be helping data scientists productionize LLM pipelines. The next, you're deep in Terraform, Helm charts, and CUDA kernels—tuning real-time latency for a Tokkio-powered digital avatar.

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Key Responsibilities

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AI Platform & DevOps (60%)

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- Architect, deploy, and maintain GPU-accelerated Kubernetes clusters using Helm, NGC containers, and custom K8s operators.
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- Build and maintain CI/CD pipelines (GitHub Actions, Jenkins, Argo CD) to enable continuous delivery of both software and models.
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- Automate infrastructure across AWS, Azure, and on-prem environments using Terraform or Pulumi.
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- Optimize GPU workloads and ensure reliability across hybrid or multi-cloud AI platforms.
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Model Lifecycle & MLOps

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- Collaborate with data scientists to containerize, benchmark, and tune LLMs, diffusion models, and multimodal pipelines.
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- Implement data governance and tracking for AI data pipelines (e.g., LakeFS, Feast).
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- Maintain feature and vector stores, ensuring reproducibility and performance of AI applications.
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Hands-on Engineering

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- Develop backend services and APIs in Python and C++ (CUDA, Triton, TensorRT-LLM) and optionally in TypeScript.
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- Integrate components from the client's digital human ecosystem: Riva (speech), Tokkio, Maxine (Audio2Face, eye contact), Omniverse.
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- Build reusable SDKs, CLI tools, and internal libraries to accelerate AI/ML workflows across teams.
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Required Qualifications

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- 10+ years of experience building and operating production-grade software systems.
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- 2+ years focused specifically on AI/ML platforms or infrastructure.
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- Proven expertise in CI/CD, GitOps, Terraform, and Helm.
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- Solid Kubernetes and Docker experience, including GPU workload scheduling.
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- Advanced Linux administration skills and experience profiling GPU workloads.
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- Expert-level Python plus one systems language (C++, Go, Rust, or Java).
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Seniority level

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- Mid-Senior level
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Employment type

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- Contract
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Job function

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- Information Technology
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Industries

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- IT Services and IT Consulting
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📌 Machine Learning Engineer (New South Wales)
🏢 NineTech
📍 New South Wales