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AI / ML Engineer (AU)

AI / ML Engineer (AU)

DroneShieldCouncil of the City of Sydney, New South Wales, Australia
13 days ago
Job description

Work with cutting edge technology, making the world a safer and more secure place. DroneShield (ASX : DRO) offers an opportunity to solve some of world’s most challenging technical problems in the Electronic Warfare, Artificial Intelligence and Machine Learning, RF sensing, Sensor Fusion and distributed systems. Working with high profile customers across militaries, government agencies, airports, critical infrastructure, law enforcement and many others.

With one of the largest listed defence company market capitalisations in Australia and having raised approximately $250m in 2024 alone, DroneShield is undergoing hypergrowth stage, fuelled by rapidly increasing use of drones for nefarious applications, from battlefield, to terrorism, to contraband delivery and commercial espionage.

This role is in the DroneShield Sydney headquarters in Sydney CBD. There are approximately 380 staff based in the 4,000sqm facility today, scheduled to grow to approximately 500 staff by end of 2026. Overseas on the ground presence includes USA, Denmark, Mexico, and UAE, as well as distributors in over 70 countries globally.

About The Role

Join a cutting-edge team at DroneShield, where you'll help develop advanced machine learning solutions that address real-world challenges. Your focus will be on applying state-of-the-art computer vision techniques to enhance our products, working alongside experts in signal intelligence and software engineering. In this fast-paced, multidisciplinary environment, we value innovation, technical excellence, and the ability to perform under pressure. You'll play a key role in maintaining and refining existing deep learning models, optimising performance, and delivering impactful solutions on tight timelines — all while solving challenging problems that make a real difference in high-stakes scenarios.

Responsibilities, Duties And Expectations

  • Maintain, refine, and extend existing deep learning models and inference pipelines.
  • Evaluate and benchmark model performance on curated datasets and real-world test cases.
  • Validate model predictions in operational or field environments and ensure deployment readiness.
  • Monitor model performance in production, identify issues, and contribute to continuous improvement.
  • Analyze datasets to identify gaps, inconsistencies, or opportunities for enrichment.
  • Collaborate with the Signal Intelligence Operations team to support data collection and annotation.
  • Work closely with software engineers to integrate and optimise ML models within production systems.
  • Write clean, maintainable, and well-documented code to support model development and deployment.

Qualifications, Experience And Skills

  • Bachelor’s degree in Computer Science, Data Science, or a related technical field (or equivalent practical experience).
  • 2+ years of hands-on experience in machine learning, specifically in computer vision applications.
  • Solid experience in developing and training deep learning models using PyTorch.
  • Demonstrated ability to tune hyperparameters (e.g., learning rate, confidence thresholds) and evaluate model performance using standard metrics.
  • Skilled in analysing, labelling, and preprocessing real-world datasets for model training and evaluation.
  • Proficient in exploratory data analysis using Pandas, and data visualisation using Matplotlib or Plotly.
  • Familiar with state-of-the-art deep learning architectures in computer vision (e.g., U-Net, ResNet, YOLO).
  • Strong Python programming skills, with knowledge of modern libraries and software engineering best practices.
  • Excellent communication and collaboration skills, with the ability to work effectively in a multidisciplinary team environment.
  • Academic research experience in deep learning and computer vision is desirable.
  • Experience with radio frequency datasets is a plus.
  • Who You Are

  • You are comfortable pushing the boundaries of ML model performance in production environments.
  • You enjoy the ML workflow end-to-end, from data collection to production monitoring.
  • You are a lifelong learner. You’re self-taught and continuously learning. You are interested in keeping up with current best practices in your areas of expertise.
  • You are experienced working with modern infrastructure and tools.
  • You are comfortable running your software in Linux environments.
  • You have an abundance of ambition and motivation to grow the company and compete with the big players in the industry.
  • You can work both autonomously and thoughtfully as a team.
  • Note for recruitment agencies : We do not accept unsolicited candidates from external recruiters unless specifically instructed.

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    Au • Council of the City of Sydney, New South Wales, Australia

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