Senior Machine Learning Engineer (Platform / MLOPs)
AUD 129K-150K (estimate) Senior-level Full Time
Tasks
- Build CI/CD pipelines
- Build LLM platform for deployment and governance
- Build scalable batch inference
- Design ML infrastructure
- Develop real time model serving
- Drive reliability and observability for production ML
- Implement distributed training pipelines
- Lead technical initiatives and mentor teams
- Maintain production Python services and libraries
- Manage ML experimentation and cost optimization
- Operate Kubernetes platforms at scale
- Own developer experience for MLOps teams
- Serve ML models to high concurrency APIs
Perks/Benefits
- Annual flu vaccinations
- Cycling friendly
- Hybrid flexibility
- In-office lunch
- Quarterly wellbeing day off
- Shower access
- Stocked kitchen
- Wellbeing and technology allowance
- Wellness subscription
Skills/Tech-stack
API Development | Amazon EKS | ArgoCD | Arize AI | Batch inference | CI/CD | Distributed Training | Docker | Evidently | GPU Acceleration | Generative AI | Google Kubernetes | Google Kubernetes Engine | Grafana | Infrastructure as Code | Kubernetes | Kubernetes Engine | LLM | Language Models | Large Language Models | Machine Learning | Model Serving | Observability | Prometheus | Python | Ray Serve | Real Time | Real-time Model Serving | SLA | SLO | Terraform | Weights and Biases | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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