• Embedded AI & Optimization: Practical experience deploying models onto hardware with strict processing, memory, or thermal constraints. Deep understanding of efficiency techniques including network pruning, weight quantization, model distillation, and hardware-level acceleration.

• ML Infrastructure & Pipeline Engineering: Grounding in full-lifecycle MLOps environments—covering data pipeline architecture, annotation workflows, synthetic data generation, version control, experiment tracking, and automated CI/CD testing frameworks.

• High-Level Communication: Skilled at detailing intricate algorithmic trade-offs, performance metrics, and technical roadmaps to varied audiences—from software engineers to commercial directors, military staff, and key external stakeholders.

Secondary / Specialist Expertise

• Acoustics & Spatial Signal Processing: Exposure to sound-event classification, direction-of-arrival tracking, microphone arrays, beamforming algorithms, or spatial audio.

• Streaming & Low-Latency Architectures: Hands-on experience with causal temporal networks, recurrent architectures, or real-time transformers optimized for continuous data processing.

• Edge Hardware & Systems Integration: Exposure to edge processing units (such as ARM architectures, NVIDIA Jetson modules, or NPUs) and feeding ML intelligence directly into situational awareness displays or command-and-control (C2) platforms.

• Defence & Mission-Critical Systems: Domain background in counter-UAS, autonomous platforms, robotics, or aerospace tech. Understanding of safety-critical AI, explainability standards, NATO guidelines, or military test and evaluation workflows.

• Fast-Paced Growth & Innovation: Experience operating within agile, scaling technology environments, with a history of supporting patent filings, technical publications, or strategic research partnerships.