Senior AI/ML Engineer (AU)

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

In this role, you will drive the design and deployment of state-of-the-art deep learning algorithms, with a strong focus on real-world applications in RF and multi-modal domains.

You’ll lead end-to-end machine learning initiatives - from research and experimentation to scalable production deployment - shaping the future of how AI is applied in defence and security. This position offers the rare opportunity to work on high-impact problems where cutting-edge ML research directly translates into operational advantage for customers worldwide.

Responsibilities, Duties and Expectations 

• Design and develop production-grade DL algorithms based on state-of-the-art research for diverse RF-based applications.
• Lead the end-to-end ML experimentation cycle, including workflow design, algorithm implementation, evaluation, and result analysis.
• Define long-term (monthly) research objectives and deliver on short-term (weekly) milestones.
• Write production-quality code following software engineering best practices (e.g., test, version control, modularity).
• Optimize model training (e.g., distributed clusters), post-training (e.g., quantization, ONNX), and inference on modern AI hardware (e.g., GPUs, TPUs, NPUs, FPGAs).
• Mentor junior team members and foster a collaborative, high-performance culture.
• Collaborate with engineering teams to integrate and deploy models into production systems.
• Ensure high standards in code quality, reproducibility, and documentation.

Qualifications, Experience and Skills 

• PhD in Computer Science or related field, or equivalent practical experience.
• Strong foundation in machine learning (ML), deep learning (DL), statistics, and optimization.
• 4+ years of experience across the full machine learning lifecycle – from data preparation and model development to deployment and monitoring.
• Expertise in three or more areas such as object detection, uncertainty estimation, out-of-distribution handling, self-supervised learning, few-shot learning, reinforcement learning, and explainable AI.
• First-author publications in top-tier AI conferences (e.g., CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML).
• Proficient in PyTorch, Python, software engineering practices, and modern ML/data science libraries (e.g., NumPy and Pandas).
• Experience working with large-scale (terabytes), high-dimensional, and heterogeneous data.
• Experience deploying models to resource-constrained environments (e.g., edge devices, embedded systems).
• Strong communication skills, with the ability to explain technical concepts to non-experts and collaborate across multidisciplinary teams.
• Experience with PyTorch Lightning is a plus.
• Familiarity with radio frequency (RF) datasets is a bonus.

Who You Are

• You thrive on pushing the limits of ML model performance in real-world production environments.
• You’re motivated by deploying complex models that make real impact.
• You enjoy the full ML lifecycle - from data collection to production monitoring.
• You’re a self-driven, lifelong learner who stays current with best practices in your domain.
• You have experience with modern ML infrastructure and tools.
• You’re comfortable running software in Linux-based environments.
• You're ambitious and motivated to help grow the company and compete at the highest level.
• You work well independently and as part of a collaborative team.

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