At a Glance
- Tasks: Design and deploy AI platforms while optimising systems for real-time performance.
- Company: Join NineTech, a leader in innovative tech solutions.
- Benefits: Competitive pay at A$90/hr, flexible work options, and growth opportunities.
- Other info: Dynamic role with a mix of DevOps, coding, and MLOps tasks.
- Why this job: Be at the forefront of AI technology and make a significant impact.
- Qualifications: 10+ years in software systems, with 2+ years in AI/ML platforms.
The predicted salary is between 90 - 90 $ per hour.
Machine Learning Engineer
This range is provided by Nine Tech. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
- Base pay range
- Direct message the job poster from Nine Tech
- We’re urgently seeking a
Senior Dev Ops ML Engineer with a rare combination of Dev Ops leadership, software engineering depth, and MLOps expertise.
The client requires someone with Dev Ops 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% Dev Ops/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 & Dev Ops (60%)
- Architect, deploy, and maintain GPU-accelerated Kubernetes clusters using Helm, NGC containers, and custom K8s operators.
- Build and maintain CI/CD pipelines (Git Hub 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., Lake FS, 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, Tensor RT-LLM) and optionally in Type Script.
- 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, Git Ops, 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
- #J-18808-Ljbffr
Machine Learning Engineer in Sydney employer: NineTech
At NineTech, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our team enjoys competitive pay, flexible working arrangements, and ample opportunities for professional growth in the rapidly evolving field of AI and machine learning. Located in a vibrant tech hub, we offer unique advantages such as access to cutting-edge technology and a supportive environment that encourages creativity and skill development.
