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Principal deep learning architect

Sydney
beBeeMachineLearning
Architect
Posted: 13 December
Offer description

Senior AI/ML Engineer Position

About the Role:

We are seeking a highly skilled Senior AI/ML Engineer to 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.

The successful candidate will 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.

* 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 objectives and deliver on short-term 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.

Key Qualifications:

* 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.

Job Requirements:

* Thrives on pushing the limits of ML model performance in real-world production environments.
* Motivated by deploying complex models that make real impact.
* Enjoy the full ML lifecycle - from data collection to production monitoring.
* Self-driven, lifelong learner who stays current with best practices in your domain.
* Experience with modern ML infrastructure and tools.
* Comfortable running software in Linux-based environments.
* Ambitious and motivated to help grow and compete at the highest level.
* Works well independently and as part of a collaborative team.

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