Senior AI Research Computing Engineer Full-time

Senior AI Research Computing Engineer

Join a world top 50 University. Be part of an inclusive, collaborative community. Be surrounded by extraordinary ideas – and the people who discover them.

The Opportunity

Project MAVERIC is a Monash-led initiative pioneering the next generation of AI-driven research infrastructure. Its mission is to accelerate discovery in addressing some of humanity's most pressing challenges, from combating disease to advancing environmental science. By uniting high-performance computing, large-scale data systems, and cutting-edge AI infrastructure, MAVERIC is redefining how researchers develop, train, and scale artificial intelligence to solve complex real-world problems.

We are seeking Senior AI Research Computing Engineers to play a pivotal technical leadership role in bringing this vision to life. In this position, you will act as the critical link between ambitious research goals and the powerful computing systems that enable them. You will architect, implement, and support the distributed AI platforms that form the foundation of MAVERIC's mission, empowering researchers to push the limits of generative AI, computational science, and cross-disciplinary innovation.

This role suits someone who excels at the intersection of software engineering, high-performance computing, and applied artificial intelligence. You'll work very closely with researchers to translate and accelerate their research using AI, turning complex scientific challenges into breakthrough computational solutions.

Key Responsibilities

• Partner with researchers across diverse domains to translate scientific goals into scalable AI/ML solutions
• Architect and optimise sophisticated AI models for high performance computing environments, implementing distributed training strategies and performance tuning at scale
• Lead development of automated MLOps pipelines using containerisation, orchestration platforms, and CI/CD practices.
• Benchmark, profile, and optimise AI applications across software and hardware layers to maximise GPU cluster efficiency
• Build research community capability through expert consultation, training programs, and technical documentation.
• Evaluate and apply emerging AI/ML technologies to novel research problems.

What We're Looking For

• Extensive experience applying AI/ML techniques to complex scientific problems
• Expert Python programming with major ML frameworks
• Proven experience designing and deploying AI workflows on HPC/GPU systems, including distributed training frameworks
• Linux system administration and HPC environment troubleshooting
• Ability to collaborate with researchers from diverse disciplines and work independently with minimal supervision

Highly Regarded Skills/Experience

• Postgraduate degree in Computer Science, Data Science, Engineering, or related discipline with extensive relevant experience; OR equivalent combination of experience and education in AI/ML and research computing
• MLOps experience: containerisation (Docker, Singularity), orchestration (Kubernetes, Slurm), CI/CD pipelines
• Knowledge of GPU architecture, performance optimisation, and profiling tools

About Monash University

At Monash, work feels different. There's a sense of belonging, from contributing to something ground breaking – a place where great things happen.

We value difference and diversity, and welcome and celebrate everyone's contributions, lived experience and expertise. That's why we champion an inclusive and respectful workplace culture where everyone is supported to succeed.

Some 20,000 staff work for Monash around the world. We have 95,000 students, four Australian campuses, and campuses in Malaysia and Indonesia. We also have a major presence in India and China, and a significant centre and research foundation in Italy.

In our short history, we have skyrocketed through global university rankings and established ourselves consistently among the world's best tertiary institutions. We rank in the world's top-50 universities in rankings including the QS World University Rankings 2026.

Today, we have the momentum to create the future we need for generations to come. Accelerate your change here.

Monash supports flexible and hybrid working arrangements. We have a range of policies in place enabling staff to combine work and personal commitments. This includes supporting parents.

To Apply

For instructions on how to apply, please refer to 'How to apply for Monash Jobs'.

Diversity is one of our greatest strengths at Monash. We encourage applications from Aboriginal and Torres Strait Islander people, culturally and linguistically diverse people, people with disabilities, neurodivergent people, and people of all genders, sexualities, and age groups.

We are committed to fostering an inclusive and accessible recruitment process at Monash. If you need any reasonable adjustments, please contact us at hr-recruitment@monash.edu in an email titled 'Reasonable Adjustments Request' for a confidential discussion.

Your employment is contingent upon the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University.

Enquiries: Joseph Pineda, Infrastructure Delivery Lead, joseph.pineda@monash.edu

Applications Close: Tuesday 25 November 2025, 11:55pm AEST