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Machine Learning Engineer building and deploying computer vision and deep learning systems in production environments. Experienced in custom neural architectures (CNNs, Transformers, GANs), automated evaluation/testing, and improving training data quality using synthetic data generation and fusion. Hands-on with OCR and integrating vision-language models (VLMs) for production perception tasks, with a strong interest in fine-tuning. Brings a robust software engineering foundation in Python, PyTorch, and Docker workflows, and focuses on data/evaluation loops to drive measurable accuracy gains in real-world, messy data.…Machine Learning Engineer building and deploying computer vision and deep learning systems in production environments. Experienced in custom neural architectures (CNNs, Transformers, GANs), automated evaluation/testing, and improving training data quality using synthetic data generation and fusion. Hands-on with OCR and integrating vision-language models (VLMs) for production perception tasks, with a strong interest in fine-tuning. Brings a robust software engineering foundation in Python, PyTorch, and Docker workflows, and focuses on data/evaluation loops to drive measurable accuracy gains in real-world, messy data.

Zane Neave

AI Engineer, Software Engineer, Data Engineer, +1

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Machine Learning Engineer building and deploying computer vision and deep learning systems in production environments. Experienced in custom neural architectures (CNNs, Transformers, GANs), automated evaluation/testing, and improving training data quality using synthetic data generation and fusion. Hands-on with OCR and integrating vision-language models (VLMs) for production perception tasks, with a strong interest in fine-tuning. Brings a robust software engineering foundation in Python, PyTorch, and Docker workflows, and focuses on data/evaluation loops to drive measurable accuracy gains in real-world, messy data.…Machine Learning Engineer building and deploying computer vision and deep learning systems in production environments. Experienced in custom neural architectures (CNNs, Transformers, GANs), automated evaluation/testing, and improving training data quality using synthetic data generation and fusion. Hands-on with OCR and integrating vision-language models (VLMs) for production perception tasks, with a strong interest in fine-tuning. Brings a robust software engineering foundation in Python, PyTorch, and Docker workflows, and focuses on data/evaluation loops to drive measurable accuracy gains in real-world, messy data.

Available to hire

Machine Learning Engineer building and deploying computer vision and deep learning systems in production environments. Experienced in custom neural architectures (CNNs, Transformers, GANs), automated evaluation/testing, and improving training data quality using synthetic data generation and fusion.

Hands-on with OCR and integrating vision-language models (VLMs) for production perception tasks, with a strong interest in fine-tuning. Brings a robust software engineering foundation in Python, PyTorch, and Docker workflows, and focuses on data/evaluation loops to drive measurable accuracy gains in real-world, messy data.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Beginner

Beginner

Language

English

Fluent

Afrikaans

Fluent

Work Experience

Machine Learning Engineer at Syos Aerospace

November 1, 2024 - Present

Deployed multiple production computer vision systems for object detection and tracking in challenging low-latency environments. Researched and developed custom CNN and Transformer architectures aligned to operational priorities. Built GAN-based thermal/RGB fusion to enhance multi-spectral perception. Established training environments with comprehensive monitoring for performance metrics and training progress. Architected robust data pipelines to inject advanced ML models and support adaptive decision-making. Integrated and constrained pre-trained vision-language models for operational perception requirements. Provided technical guidance and oversight on system design and ML architecture. Collaborated on multi-domain autonomy architecture for multi-UXV operations with integration points for ML across vehicles and ground control. Supported robotics integration using mechatronics knowledge bridging mechanical, electrical, and software systems.

Software and Artificial Intelligence Engineer at Marine AI

April 1, 2023 - December 1, 2024

Developed and deployed real-time computer vision systems for marine object detection, tracking, and recognition. Implemented automated testing frameworks for trained models to improve accuracy assessment workflows. Enhanced training dataset creation by fusing labeled data with synthetically generated samples to improve robustness. Performed model testing, validation, and optimization for improved predictions. Applied OCR to extract text from images and documents as part of broader vision workflows. Automated parts of the ML pipeline via custom scripting to increase efficiency. Designed and implemented interactive 3D interfaces for visualizing vision outputs. Applied ML techniques across supervised/unsupervised learning, NLP, image recognition, and sentiment analysis. Conducted research on emerging AI/ML technologies and communicated findings to cross-functional teams.

Research Student (Honours Project) at Robotics Plus

March 1, 2022 - November 1, 2022

Completed the Engineering Honours project with Robotics Plus. Advanced Python and C++ skills and used ROS2 and Docker for robotics development. Applied deep learning to improve object detection accuracy. Developed and deployed a tracking system for monitoring detections. Calibrated stereo cameras to generate high-quality point clouds. Implemented a custom test rig to meet project needs. Strengthened code management through proactive Git usage and improved productivity in VS Code and Ubuntu/Linux environments. Conducted research into automation and robotics technologies.

Research Student at University of Waikato

March 1, 2022 - February 1, 2023

Designed and deployed a vision system for optimal performance on the University’s Rock Melon Harvester. Explored research topics and produced detailed summaries while deepening Python and C++ proficiency. Built Docker-based isolated workspaces to support ROS2 development. Implemented neural networks to improve detection accuracy and added tracker, sizing algorithm, occlusion checks, and segmentation techniques. Applied OCR for text extraction within the vision pipeline. Created a robust outdoor-capable rig handling weather and lighting variability. Improved code documentation and management practices, and orchestrated Git server setup for efficient version control.

Project Engineering Intern at Robotics Plus

November 1, 2021 - November 1, 2022

Applied mechanical, electrical, and software expertise to assemble robotic systems and support installations. Performed camera calibration, system integration, and electrical component assembly. Streamlined robotics assembly processes by improving documentation, workflows, and production models. Managed multiple concurrent projects while supporting robot assembly and troubleshooting. Developed strong collaboration, organizational, and time management skills in production environments.

Project Engineering Intern at Robotics Plus

November 1, 2020 - February 1, 2021

Gained hands-on experience with advanced robotics and control systems for agricultural applications. Built practical knowledge in mechanical and electrical system integration. Supported production team operations and contributed to process improvements.