
Senior Data Engineer
6 days ago
About the role
Our Client is seeking a Senior Data Engineer to join our team in Sydney, Australia. Reporting to the SensorFusionAI (SFAI) Team Lead, you will develop the core data pipelines and tools that turn real-world, multi-sensor data into actionable AI intelligence — powering systems that operate in the world's most complex and high-stakes environments.
This is a unique opportunity to apply your data engineering expertise in a deeply mission-driven company, working with diverse, high-volume, real-world sensor data (e.g., RF, optical, radar) in dynamic environments.
Responsibilities, Duties and Expectations
- Design, develop, maintain and/or refine internal software tools used for processing data, workflow automation, benchmarking and testing the SensorFusionAI engine.
- Analyse real-world sensor data, identify critical parameters and plan data collection strategy ensuring our target classification models remain at the cutting edge.
- Lead data analysis during new sensor integrations, evaluating detection accuracy and their fit for use within our sensor fusion framework.
- Liaise with drone pilots, QA and field-service engineers to collect real-world data from our multi-sensor installations.
- Oversee data annotation processes and quality control to ensure consistent, model-ready datasets.
- Implement and maintain automated workflows and pipelines (e.g., Git, CI/CD, MLOps, DataOps) to uphold the highest performance and quality standards.
- Continuously improve data engineering pipelines to ensure performance, scalability, and reliability.
- Work in close collaboration with relevant stakeholders to troubleshoot and resolve bug/issue reports.
- Maintain a high standard of software quality through documentation, testing, and code reviews.
- Collaborate closely with other engineers and become a valued member of an autonomous, cross-functional team.
Qualifications, Experience and Skills
- BS degree in Computer Science, Mathematics or similar technical field of study or equivalent practical experience
- Minimum 3 years of experience in a professional Software Engineering environment
- Strong background in data engineering
- Demonstrated experience in creating automated workflows (CI/CD, DataOps) and AI/ML pipelines (MLOps)
- Proficiency in an object-oriented programming language with strong expertise in one or more general purpose programming languages (ideally Python/Golang)
- Strong grasp of data structures, algorithms, and the application of mathematics and physics in software development
- Familiarity with Linux and containerisation
Nice to have
- Experience in AI or Machine Learning projects
- Proficiency in C++, meta build tools (CMake) and unit testing frameworks
- Experience developing data intensive real-time applications and/or GPU based processing systems (TensorRT, CUDA…)
- Knowledge of sensor fusion and object tracking algorithms
Who you are
- You have a strong foundation in software and data engineering, and you are confident in designing scalable systems that ingest, process, and transform large volumes of real-world sensor data.
- You have hands-on experience building tools, pipelines, or frameworks that support AI/ML workflows.
- You have worked across the entire data lifecycle — from raw ingestion and transformation to preparing clean, labeled datasets for model training and validation.
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