Senior Staff Deep Learning Engineer (R5675)

Shield AI, a venture-backed defense-tech company, is hiring to expand its Melbourne onsite team with a Senior Staff Deep Learning Engineer (R5675). The company builds perception and autonomy technologies, including Hivemind software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality tools, with a global footprint across multiple regions. The role sits in Melbourne, Australia, on a full-time, onsite basis, and would suit someone who wants to shape perception capabilities for both autonomous and non-autonomous platforms.

In this position you’ll work at the intersection of research and real-world deployment, translating deep learning insights into practical perception solutions that run on edge devices. You’ll join a team of deep learning engineers to architect and build scalable tools that scale up DL operations, while staying current with the latest literature and contributing to several R&D projects. The environment rewards hands-on problem solving and collaboration with cross-functional teams.

If you’re excited by edge AI for defence and civilian applications, enjoy translating theory into field-ready systems, and want to contribute to a team that moves ideas from concept to impact, this could be a strong fit.

Edge perception in practice

You’ll research, design and implement perception capabilities, taking ideas from concept into field-ready solutions for real-world use. The work includes deploying the company’s AI stack to edge devices and partnering with fellow deep learning engineers to craft tools that help scale DL operations. You’ll also keep pace with the literature and actively take part in a range of research and development projects to push the boundaries of perception technology.

The role emphasizes collaboration and practical impact, with opportunities to influence both the underlying algorithms and the way they are applied on hardware in demanding environments. You’ll contribute to a team that values rigorous experimentation and pragmatic implementation, delivering results that support ongoing operations worldwide.

What we need from a senior staff deep learning engineer

• 3 – 5 years of industry experience delivering deep-learning solutions for computer vision tasks
• Solid grasp of convolutional networks and/or transformer models used for classifying, recognising or segmenting objects
• Experience working with recent Foundation Models
• Hands-on with building novel DL architectures using frameworks such as TensorFlow, Caffe, PyTorch or similar
• A relevant bachelor’s, master’s or doctoral degree in computer science or related fields

Nice-to-haves

• Publications in leading Computer Vision or AI conferences and journals such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, PAMI or JMLR
• C++ and/or Python development experience
• Deep understanding of the latest DL architectures for computer vision and image processing
• Experience with object detection and target tracking, SLAM, 3D reconstruction, camera calibration, behaviour analysis, foundation models, vision-language models, large multi-modal models, automated video surveillance or related fields
• Experience deploying DL models in embedded production contexts, including structured and unstructured pruning, network quantisation and performance tuning
• Experience maintaining and/or setting up MLOps systems and services
• Experience mentoring junior engineers or researchers in related fields

Pay, benefits and practical details

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check.

Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. The company commits to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or veteran status. If you have a disability or special need that requires accommodation, please let them know.