Machine Learning Engineer

Machine Learning Engineer

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

Base pay range

A$90.00/hr - A$90.00/hr

Direct message the job poster from NineTech

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

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

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

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

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.

Key Responsibilities

AI Platform & DevOps (60%)

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

Model Lifecycle & MLOps

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

Hands-on Engineering

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

Required Qualifications

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

Seniority level

• Mid-Senior level

Employment type

• Contract

Job function

• Information Technology

Industries

• IT Services and IT Consulting