Job Description MLOps Engineer - Sensor Fusion Tools $140-160,000 super Sydney, hybrid work environment Is it a bird? Is it a plane? It’s not Superman. It could be a drone though, but is it friend or foe? Working here, you’ll tackle hard, ambiguous engineering problems involving noisy data, sensor complexity, and edge-case detection that answer that question. You'll work on some of the toughest challenges in the field, giving you the chance to sharpen your problem-solving skills and work with cutting-edge technology. You’ll balance synthetic data with real-world field data to build resilient and adaptive models. This will give you hands-on experience with advanced data techniques that are highly sought after in the AI and machine learning space. Develop robust internal tools for use by QA, field teams, and annotators, tools that are directly tied to product success. You'll see the direct impact of your work, which is rare in larger organisations. Enjoy hybrid working with modern purpose-built offices. If you’re working late, dinner and an Uber home are on the company. What you'll do You'll design, build, and maintain advanced software tools that power the SensorFusionAI engine, enabling accurate detection, benchmarking, and validation of real-world and synthetic data in complex environments. You'll work at the intersection of software engineering, simulation, and AI tooling, helping to operationalise cutting-edge technology that keeps people and assets safe from emerging drone threats. Specific areas you'll be involved include: Simulation & Synthetic Data Tools: Maintain and enhance the physics-based Python simulator used to generate synthetic drone detections, ensuring integration with the end-to-end sensor fusion testing pipeline. Benchmarking & Performance Evaluation: Develop and improve tools to benchmark the accuracy and performance of the SensorFusionAI engine, supporting hyperparameter tuning and model evaluation using ClearML or similar platforms. Automation & Pipelines: Design and implement automated CI/CD, MLOps, and DataOps workflows to support scalable and repeatable development and testing processes. Annotation & Data Review Tools: Extend and optimise internal tools for data annotation review and validation, improving usability and performance for data teams collecting and classifying real-world drone data. Field Data Support & Gap Analysis: Collaborate with drone pilots and field engineers to collect and analyse real-world test data, identifying missing data types and proposing tests to reflect environmental complexity and edge cases. What you'll need 5 years of engineering experience Strong Python skills; C++ or Java experience a plus Experience with CI/CD and MLOps/DataOps pipelines (e.g. ClearML) Background in simulation, benchmarking, or digital twin environments Proficient in data analytics, processing, and visualisation Solid understanding of algorithms & data structures Please click the ‘Apply’ button. Don’t worry if your resumé isn’t up to date. Just send what you have and we’ll deal with that later.