An Australian agency client is currently experimenting and building capability with Large Language Models (LLMs) and Computer Vision (CV) techniques at large scale for the purpose of assessing their applicability to the Defence context.
Existing initial demonstrators have shown great promise and the agency is now in need of four machine learning engineers to further develop, accelerate and mature these capabilities.
Successful applicants will be working with leading-edge hardware and ML technologies, demonstrating the art of the possible and working toward bringing ML based technology into the Defence domain in support of Defence’s mission and capabilities.
The Machine Learning Engineers will be required to work as part of an integrated team spanning ICT professionals and engineers, Researchers, Defence Operators and Analysts. They will work as part of a team designing and developing machine learning systems, implementing appropriate ML algorithms, conducting experiments and demonstrating outcomes and ML based opportunities to the Defence stakeholders. They will be working with DSTG data sets to create models, perform statistical analysis, to train and retrain systems to optimise performance with a goal to build efficient self-learning applications and contribute to Defence’s advancements in artificial intelligence.
Activities and Deliverables
The Machine Learning Engineers will work in the design and development of Defence focused machine learning and deep learning systems, running machine learning tests and experiments while developing and implementing appropriate ML algorithms. This will encompass:
- study and transformation of data science prototypes;
- design of machine learning systems;
- development of machine learning applications according to requirements;
- selection of appropriate datasets and data representation methods;
- performance of statistical analysis and fine-tuning using test results;
- executing train and retrain systems as necessary; and
- extend existing internal DSTG ML libraries and frameworks.
They must be willing and able to support the agency in activities relating to its operational mandate and objectives.
Key required technical skills and experience include:
- Experience in software development & machine learning.
- Experience in the use of machine learning methods on multi-GPU platforms.
- Extensive Linux knowledge.
- Ability to communicate effectively and tailor presentation style and messaging to be relevant to a range of audience level of knowledge, skills and experience.
- Sound interpersonal skills including the ability to work as a productive member of a team and communicate effectively with colleagues and clients across multiple organisational levels.
- Effective written and verbal communication skills.
- Respond strongly and positively to challenging work and deadlines
- Experience in the use and development of machine learning methods at scale within standalone or multi-GPU and multi-node configurations.
- Experience in MLOps and ModelOps software and associated engineering practices.
- Experience with best practice development methodologies and practices such as Agile, DevOps, and Configuration-As-Code.
- Understanding of data structures, data modeling and software architecture.
- Knowledge of math, probability, statistics and algorithms as applicable to the ML context.
- Ability to write code in Python, Java or R.
- Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikitlearn).
- Demonstrated analytical and problem-solving skills.
- Previous experience within the Defence environment.
- Familiarity with Defence IT security policies and concepts.
- Security Clearances for Nominated Personnel.
All engaged Service Personnel providing the services in all categories at Edinburgh and Fishermans Bend must have a minimum NV-1 (Negative Vetting level 1), and there is a strong preference for NV2 (Negative Vetting Level 2).