First listed on: 11 January 2022
Computer Vision Team Lead 


EL 2 (S&T 6)
$123,159 - $147,828 (plus Super)
Edinburgh - SA 

The Role

  • Inspire and mentor a small team of machine learning researchers and engineers
  • Contribute to innovation of scientific research in a Defence environment
  • Enjoy flexible working arrangements

This exciting role is at the intersection of space and artificial intelligence. It involves leading a small high-performing team of data scientists and machine learning researchers in conducting applied research into computer vision methods for automated analysis of earth observation imagery. The ideal applicant will have a track record in computer vision, image processing or machine learning methods, as well as a passion for space and geospatial data. In this role you will contribute to a culture of innovation that drives our More Together: Defence Science and Technology Strategy.

As the Computer Vision Team Lead, you will:

  • Utilise your experience in computer vision, machine learning, or artificial neural networks to coordinate a research program into one or more of the following:
    • Target detection, classification and tracking models for geospatial image and video data;
    • Techniques to optimize machine learning model size and processing performance; and
    • Classical computer vision, image processing and geospatial techniques. 
  • Produce models and algorithms using Python and modern data science tools for computer vison and image processing (PyTorch/TensorFLow,OpenCV, etc).
  • Support the continual improvement and deployment of models/architectures/algorithms into operations through the DevOps and MLOps lifecycle.
  • Supervise and mentor staff to promote a healthy culture that values staff, innovation and excellence in science.
  • Manage allocated resources, set work area priorities, manage workflows, develop strategies and evaluate business outcomes.
  • Work collaboratively with industry, academia and other research agencies.
  • Report research findings to Defence partners and the scientific community through high quality scientific reports, briefs, publications and presentations.

A merit pool will be created from the list of suitable applicants which may be used to fill future positions in the event a position becomes vacant within the 12 months from gazettal date of this position.

About our Team
Intelligence, Surveillance and Space Division (ISSD) undertakes internationally-recognised research and development into technologies aimed at enhancing national capability for Defence and national agency decision makers.

The role is within Automated Imagery Analysis (AIA) group, within Space Intelligence branch in ISSD.

Automated Imagery Analysis group conducts research into the automated processing of oblique and overhead imagery data at the edge, and in the centre, to deliver tactical, operational and intelligence information using computer vision and machine learning. It performs research into the vulnerabilities and protection of the automated processing techniques.

More information about our division and its Branches is available here – ISSD

Our Ideal Candidate
We are looking for a motivated team player who is able to understand the broad strategic context and has sound stakeholder engagement skills.

To succeed in this role, you must be able to demonstrate the following:

  • Specialised knowledge and research experience in computer vision, image processing or machine learning to generate new knowledge and produce enhanced capabilities for clients and sponsors
  • Ability to lead the development of Science & Technology (S&T) initiatives
  • Ability to think strategically, problem solve and operate with considerable autonomy to achieve corporate impact
  • Sound communication skills, both written and verbal, with an ability to foster effective stakeholder relationships
  • Adaptability and resilience in a dynamically changing environment
  • Working collaboratively across different teams, harnessing diverse views and encouraging an inclusive team culture
  • Supervise, mentor and develop staff
  • Commitment towards ongoing self-improvement and professional development

Application Closing Date: Monday 31 January 2022

For further information please review the job information pack, reference DSTG/06004/21 on


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