AI Operations Engineer
Expired
This role has expired and is no longer accepting applications. Browse similar roles →
M&T Resources
Sydney NSW
Full Time
Apply for this job
Posted 8 months ago
This role is expired
These roles are hiring now
View all AI roles →Senior Research Scientist - Design Generation
Canva
Sydney, NSW
- Train and evaluate generative models (LLMs) for design generation at scale
- PhD + 2+ years industry experience or 6+ years industry experience
- LLM/MLLM fine-tuning, multi-GPU training, large-scale data pipelines
Posted 3d ago
Senior AI Engineer (Risk & Payments)
Airwallex
Melbourne, VIC
hybrid- Design and deploy AI agents for risk management and payment workflows
- 2+ years applied AI/ML engineering with production deployments
- Python, PyTorch, LangChain, LlamaIndex, RAG, agent orchestration
Posted 2d ago
Data Scientist
Nous Group
Brisbane, QLD | Canberra, ACT | Melbourne, VIC | Perth, WA | Sydney, NSW
- Apply data science to complex strategic challenges across diverse sectors
- Experience with statistical and analytical techniques
- R or Python, statistical modelling, data visualisation, SQL
Posted 5d ago
Lead Data Scientist - AI Technical Solutions
Quantium
Sydney, NSW
hybrid- Lead design & delivery of production-grade generative AI solutions
- 7+ years in data science, AI, ML solution delivery or technical consulting
- GenAI, LLMs, Python, LangChain, AWS/Azure/GCP, Airflow, team leadership
Posted 4d ago
Our client is at a pivotal stage in its AI journey. With their first AI products already serving customers, they are scaling rapidly across business units.
This role is your chance to help build the operational foundations, best practices, and processes that will define how we run AI for years to come.
Requirements:
- Degree in Computer Science, Engineering, Data Science, or related field
- 5+ years in MLOps/DevOps/SRE with proven AI/ML production experience
- Expertise in cloud ML platforms (GCP, Vertex AI) for deployment, scaling, and infrastructure
- Solid DevOps practices: CI/CD, IaC, Docker, Kubernetes, automation (Python/Bash)
- Monitoring/observability for AI/ML services: performance, drift, system health
- ML governance: versioning, compliance, best practices in regulated environments
- Data quality & streaming: validation, event-driven architectures, real-time pipelines
- Experience in regulated industries (financial services preferred)
- Strong communication skills
- Excellent organization and time management
- Able to work independently