Australian Citizens With NV1 Clearance residing in Australia only respond 

• Contract start 01 November 2023 to 8 months, 2 x 12 months extensions.
• Australian Citizen, NV1 Clearance, Edinburgh (Northern suburbs of Adelaide) and Fishermans Bend (Melbourne), Flexible working arrangements by negotiation role.

Send your responses to jobs@softtestpays.com

Overview

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 DSTG in activities relating to its operational mandate

and objectives.

Skills and Experience of Candidates

6.1 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.

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 NV-2 (Negative Vetting Level 2).

Every application requires to address selection criteria as part of application submission.

Applicants should provide

A brief summary (up to 3 pages) of how they meet the technical requirements.

An up-to-date resume.

Details of 2 recent referees.

Essential Criteria

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 scikit-learn).

Demonstrated analytical and problem-solving skills.

Desirable Criteria

Previous experience within the Defence environment.

Familiarity with Defence IT security policies and concepts.

Security Clearances for Nominated Personnel.