AI & Solar Performance Engineer

The Opportunity:
As an AI & Solar Performance Engineer, you will contribute to the design and delivery of AI-driven systems that integrate solar field data for intelligent monitoring, fault diagnostics, and automation. The role applies professional engineering judgement while working under the guidance of senior engineering staff on complex engineering and research projects. It applies physics-based modelling, agentic AI, and engineering principles to help transform raw plant data into actionable insight, supporting human operators and improving asset performance across the solar value chain.

This role sits at the intersection of process engineering, control systems, and data-driven diagnostics for utility-scale solar assets. Assist the team in the application of engineering principles and technologies to an emerging, cross-disciplinary field spanning solar performance, control systems, and data engineering.

This role reports to Dr Jim Joseph John, Faculty of Engineering and has no direct reports

• Salary, Level 5: From $92,265- $104,401 per annum + 17% superannuation
• Full Time (35 hours)
• Fixed term contract until January 2028 (18 months)
• Location: Kensington – Sydney, Australia (on campus attendance 3 days a week minimum required)

About UNSW:
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.

Skills & Experience:

• A recognised bachelor’s degree or higher in a relevant engineering discipline (e.g. electrical, mechanical, mechatronic, process/chemical, renewable energy or photovoltaic engineering). Relevant experience in solar energy technology is highly desirable.
• Eligibility for membership of Engineers Australia, or an engineering qualification assessable as comparable by Engineers Australia (desirable).
• Sound Python programming skills, including the ability to write code and contribute to backend systems and data pipelines.
• Exposure to solar PV performance modelling (performance ratio, yield, fault detection).
• Foundational knowledge of machine learning, data analysis, and time-series data methods.
•  Exposure to, or interest in, AI agents and/or LLM-based systems for diagnostics or automation.
• A working understanding of process engineering, control systems, and thermodynamics as applied to energy systems.
• Some experience integrating, or a willingness to learn to integrate, software and analytics with SCADA, historian, cloud, and operational systems.
• Ability to interpret engineering drawings, single-line diagrams, and technical specifications.
• Understanding of the evolution of commercial solar technology over time and its impact on plant performance and operations.
• High-level communication skills and the ability to network effectively and interact with a diverse range of staff, students, and industry partners.

To Apply: Please click the apply now button and submit your CV, Cover Letter and Responses to the Skills and Experience. You should systematically address the Skills and Experience listed within the  Position Description in your application. 

Job queries contact: Katherine Molloy, Talent Acquisition Consultant
E: katherine.molloy@unsw.edu.au  (applications to the address cannot be accepted, please apply online)

Applications close: 11:55 pm (Sydney time) on Monday 7 September 2026

UNSW is committed to evolving a culture that embraces equity and supports a diverse and inclusive community where everyone can participate fairly, in a safe and respectful environment. We welcome candidates from all backgrounds and encourage applications from people of diverse gender, sexual orientation, cultural and linguistic backgrounds, Aboriginal and Torres Strait Islander background, people with disability and those with caring and family responsibilities. 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.