Work with cutting edge AI 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 rapidly growing counter-drone sector.  

Our customers operate in some of the most challenging and high-stakes environments in the world, including military organisations, government agencies, airports, critical infrastructure operators, and law enforcement. Protecting airspace in these settings requires technology that performs under pressure and teams that understand what’s at stake. At DroneShield, employees work at the leading edge of counter-drone innovation, helping to address real-world security challenges as drone threats continue to evolve globally.

With one of the largest listed defence company market capitalisations in Australia, now part of the ASX200 index, DroneShield is experiencing a period of hypergrowth. Revenue has surged from A$57 million in 2024 to over A$217 million in 2025, representing growth of more than 400% year-on-year, with record profitability and cashflow. The total addressable global market for counter-drone is assessed at approximately $100 billion, and is currently at the nascent stage with much of the growth still to come, with DroneShield well positioned as a global market leader, and the only public listed pure-play business in this sector.  

The company has grown from 11 employees in 2017 to over 450 staff globally today, and is on track to reach around 550 by the end of 2026. This expansion includes investment of over A$50 million annually in R&D, a global pipeline exceeding A$2.5 billion, and continuous scaling of production capacity to meet accelerating demand. 

The role is based at DroneShield’s central Sydney headquarters. Overseas on-the-ground presence includes Virginia (USA), Netherlands, Denmark, Mexico and Dubai, as well as distributors in over 70 countries worldwide.

About the role

DroneShield is seeking an AI/ML Engineer to join our growing team in Sydney, Australia. Reporting to the SensorFusionAI (SFAI) Team Lead, you will play a key role in developing custom, multi-sensor AI models that contribute towards sensor fusion and provide real-time actionable intelligence to end users across defence, security and critical infrastructure domains.

You will work on applied AI research and development, solving real-world sensing challenges where off-the-shelf approaches are insufficient, and translating experimental models into production-ready capabilities.

Responsibilities, Duties and Expectations 

• Maintain, improve and extend existing custom AI models, and architectures
• Research, design and develop custom AI models and architectures to solve real-world challenges under constrained, noisy or adversarial conditions
• Define, design and run structured experiments including benchmarking and ablation studies to evaluate model performance, iterating rapidly from prototype to validated solution using real-world data
• Collaborate with data engineers, MLOPS engineers and AI/ML engineers to develop or upgrade data collection, ETL and annotation tools and workflows for new and improved models
• Contribute to the development of new Actionable Intelligence features utilising the integrated AI models
• Contribute to the development of MLOPS and model benchmarking pipelines and workflows
• Work closely with software engineers to deploy, integrate and optimise ML models for inference within DroneShield’s production systems
• Monitor and optimise model performance post-deployment, investigating issues and driving continuous improvement based on real-world feedback
• Write clean, maintainable and well-documented code, following modern software engineering and AI/ML best practices (testing, CI/CD, code reviews)
• Contribute to the long-term AI/ML roadmap of DroneShield’s world-class counter-drone solutions

Qualifications, Experience and Skills 

• Bachelor’s degree (or higher) in Computer Science, Data Science, Artificial Intelligence, or a related technical field or equivalent practical experience
• Minimum of 3 years of professional, hands-on experience researching, developing, training and deploying custom machine learning models, including traditional, deep learning, and attention-based transformer architectures
• Proven experience developing custom or non-standard model architectures, or adapting existing techniques to domain-specific problems
• Proficiency in Python; knowledge of at least one object-oriented programming language (e.g. Go, C++) is favourable
• Strong experience with ML frameworks such as PyTorch, TensorFlow, Scikit-Learn and familiarity with model optimization and conversion tools (e.g. ONNX, TensorRT)
• Proven experience with model evaluation, metrics, and inference optimization across various platforms
• Experience working with real-world, noisy, incomplete or adversarial datasets
• Experience with CUDA, distributed or real-time inference systems and GPU acceleration
• Familiarity with containerization and orchestration using Docker
• Proficiency in Linux-based development and runtime environments
• Experience designing and implementing automated CI/CD workflows is favourable

Who you are

• You are a self-driven learner, always seeking to improve and stay at the forefront of your field. 
• You excel in fast-paced, mission-critical environments with a strong sense of purpose. 
• You are a clear communicator capable of bridging technical and non-technical discussions. 
• You are collaborative and team-oriented, contributing positively to shared problem solving. 
• You take ownership of your work, driving solutions from concept to deployment. 
• You are proactive in influencing technical direction and contributing to strategic decisions. 

Note for recruitment agencies: We do not accept unsolicited candidates from external recruiters unless specifically instructed.

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