University of Melbourne
DevOps Engineer
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✓ Actively Hiring
📍 Carlton
💼 Full Time
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Job at a Glance
- Category
- IT Engineer & Developer
- Location
- Carlton, Victoria, Australia
- Salary
- Check with seller
- Job Type
- Full Time
- Company
- University of Melbourne
- Status
- Open & Active
Job Description
We are seeking a DevOps Engineer with a solid background in Neo4j, InfluxDB, to join our AI-driven engineering team.
You will play a key role in deploying, managing, and optimizing data-intensive pipelines that power time series analytics, graph databases, and generative AI systems. A working knowledge of deep learning frameworks is highly desirable.
Responsibilities
Design, deploy, and manage production-grade Neo4j and InfluxDB environments.
Automate deployment and monitoring of machine learning pipelines and inference APIs.
Implement robust logging and time series monitoring strategies using InfluxDB.
Work with data scientists to containerize and scale training/inference workloads (e.g., using Docker, Kubernetes).
Ensure security and performance best practices in cloud or on-prem environments.
Required Skills
4 to 8 years of DevOps/SRE experience.
Hands-on with Neo4j (Cypher, indexing, backups, clustering).
Strong experience with InfluxDB and time-series data handling.
Proficient with Docker and Kubernetes.
Solid scripting skills in Python.
Cloud infrastructure experience with AWS.
Nice to Have
Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
Education
Bachelor’s or Master’s in Computer Science, Engineering, or a related field, or equivalent practical experience.
Job Type: Part-time
Pay: $60.00 per hour
Work Authorisation:
Australia (Required)
Work Location: In person
You will play a key role in deploying, managing, and optimizing data-intensive pipelines that power time series analytics, graph databases, and generative AI systems. A working knowledge of deep learning frameworks is highly desirable.
Responsibilities
Design, deploy, and manage production-grade Neo4j and InfluxDB environments.
Automate deployment and monitoring of machine learning pipelines and inference APIs.
Implement robust logging and time series monitoring strategies using InfluxDB.
Work with data scientists to containerize and scale training/inference workloads (e.g., using Docker, Kubernetes).
Ensure security and performance best practices in cloud or on-prem environments.
Required Skills
4 to 8 years of DevOps/SRE experience.
Hands-on with Neo4j (Cypher, indexing, backups, clustering).
Strong experience with InfluxDB and time-series data handling.
Proficient with Docker and Kubernetes.
Solid scripting skills in Python.
Cloud infrastructure experience with AWS.
Nice to Have
Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
Education
Bachelor’s or Master’s in Computer Science, Engineering, or a related field, or equivalent practical experience.
Job Type: Part-time
Pay: $60.00 per hour
Work Authorisation:
Australia (Required)
Work Location: In person
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