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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