- Employment Type: Full-Time (35-hour week)
- Duration: Fixed Term contract until December 2025
- Remuneration: Level 8 From $123k - $133k + 17% superannuation & leave loading
- Location: Kensington NSW (Hybrid Flexible Working)
Why your role matters
The ML/AI Ops Engineer, Special Projects, plays a critical role within the Pro Vice-Chancellor Education (PVCE) Innovation Team. This position is central to designing, implementing, and maintaining scalable cloud-based Machine Learning (ML) and Artificial Intelligence (AI) operations that support robust, sustainable, and reliable enterprise-level educational analytics. By operationalising ML/AI applications and distributed systems, the role contributes to strategic educational projects aimed at fostering data-driven innovation and enhancing the student experience at UNSW.
This role collaborates with agile teams of Data Scientists and Education Designers, supporting the delivery of approved and strategically aligned educational initiatives and applications. Key responsibilities include establishing and managing ML/AI Ops processes, developing and monitoring automated pipelines for data collection, transformation, and provisioning, and assisting with Azure Resource Management. The focus spans scalability, performance, reliability, cost efficiency, and cybersecurity. Additionally, the role demands a proactive approach to staying current with emerging trends and technologies in the ML/AI field.
Reporting to the Project Manager, Special Projects, and maintaining a dotted line to the Chief Data & Insights Officer for technical and design guidance, this role ensures the effective integration of advanced analytics into educational solutions. While there are no direct reports, the position requires a high level of expertise, innovation, and leadership in the implementation of ML/AI-driven systems.
Specific accountabilities for this role include:
- Consult and liaise with project leaders, management team, data scientists, education designers and other stakeholders to understand business needs and lead ML/AI systems planning, delivery and support using the University approved platforms.
- Collaborate with divisions, faculties and schools to understand their data and ML/AI systems needs and provide relevant advice or data solutions that meet their requirements.
- In collaboration with UNSW IT and UNSW Planning & Performance (UPP) operate and configure data infrastructure resources to develop and deploy multiple and complex ML/AI systems in production environments, efficiently using cloud services or on-premises infrastructure based on requirements.
- Develop, implement and maintain automated ETL/ELT pipelines for data acquisition, integration, cleaning, pre-processing, training and testing of complex ML/AI
About You:
- Postgraduate degree in Computer Science, Software Engineering or related field with relevant experience in data engineering, cloud engineering, business intelligence development, or an equivalent level of competency gained through any combination of education, training or experience.
- Advanced programming skills and experience in the implementation and management of structured and unstructured big data analysis. Proven experience in SQL, Python and PySpark is highly desirable.
- Advanced cloud computing skills and experience in the development and implementation of ML/AI data resources and pipelines in cloud-based computing environments. Proven experience in Azure Machine Learning, OpenAI Studio and Azure Functions and are highly desirable.
- Demonstrated theoretical understanding and proficiency in the development and implementation of prompt engineering for generative AI solutions. Proven experience in deploying open-source Large Language Models (LLMs) on cloud-based instances and Natural Language Processing (NLP) applications are highly desirable.
- Demonstrated ability to understand and implement ML/AI Ops and MML Ops principles and practices for automating the end-to-end Lifecyle and handling of multi-modal data integration of ML/AI systems. Proven experience in Azure DevOps is highly desirable.
- Demonstrated proficiency in designing, implementing and maintaining automated ETL/ELT, CI/CD and deployment pipelines. Proven experience in Kubernetes for orchestration and Docker for containerisation are highly desirable.
- Demonstrated ability to monitor, log and optimise ML/AI systems for reliability, scalability, debugging, troubleshooting, performance and cost-efficiency. Proven experience in Infrastructure as Code (IaC) tools such as Azure ARM templates for provisioning and managing infrastructure resources is highly desirable.
- Demonstrated ability to define, develop and implement operational explainability and interpretability technics for complex ML/AI systems. Proven experience in Explainable AI, Responsible AI are highly desirable.
The Organisation
UNSW isn’t like other places you’ve worked. Yes, we’re a large organisation with a diverse and talented community; a community doing extraordinary things. But what makes us different isn’t only what we do, it’s how we do it. Together, we are driven to be thoughtful, practical, and purposeful in all we do. If you want a career where you can thrive, be challenged and do meaningful work, you’re in the right place.
Benefits and Culture:
UNSW offers a competitive salary and access to UNSW benefits including:
- Flexible working
- Additional 3 days of leave over the Christmas period
- Access to lifelong learning and career development
- Progressive HR practices
- Discounts and entitlements
More information on the great staff benefits and culture can be found here.
To Apply: Please submit your CV, Cover Letter and responses to the selection criteria (the skills and experience in the PD) via the ‘Apply Now’ button.
A copy of the Position Description can be found on JOBS@UNSW.
Applications close: Monday 6th January 2025 at 11.55pm.
Get in Touch: Chloe Gane – Talent Acquisition Consultant
chloe.gane@unsw.edu.au
Applications cannot be accepted if sent directly to the contact listed.
UNSW is committed to equity diversity and inclusion. Applications from women, people of culturally and linguistically diverse backgrounds, those living with disabilities, members of the LGBTIQ+ community; and people of Aboriginal and Torres Strait Islander descent, are encouraged. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.
