Pieter Cawood | Lead Software & ML Engineer

Hi, I'm Pieter Cawood.

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Machine learning and software engineer with extensive experience in industrial automation, developing AI-driven solutions for the 4th Industrial Revolution.

About

I am a machine learning and software engineer with a diverse background and extensive experience in industrial automation. With a passion for developing software solutions for the 4th Industrial Revolution, I embrace data-driven, edge, and cloud-based techniques to tackle challenging problems.

At Infinite Process Solutions, I serve as Lead R&D Software Engineer, where I architect MLOps and AI-based predictive maintenance solutions. My work includes designing cloud infrastructure, building data pipelines with Python and Airflow, and deploying deep learning models with fast.ai and MLFlow.

Over the years, I have developed a deep understanding of various software standards in industrial automation. My experience spans leading and guiding teams through complex projects, including the development, offline programming, site commissioning, and support of over 100 discrete and batch manufacturing lines.

Languages: Python, C#, VB.NET, SQL, JavaScript, TypeScript, PLC Programming
ML & AI: TensorFlow, PyTorch, fast.ai, Scikit-learn, XGBoost, LightGBM, CatBoost, MLFlow
Cloud & DevOps: Azure ML, Azure Databricks, Azure Data Factory, Docker, CI/CD, Apache Airflow
Frameworks: Django, Node.js, React.js, Next.js, .NET (WPF, MVC, WCF, EF)
Industrial Automation: Siemens PLC/HMI, Rockwell Logix5000, Beckhoff TwinCAT, SCADA Systems
Databases: SQL, NoSQL, MongoDB

My academic journey includes an MSc in Artificial Intelligence (with distinction) and BTech in Electrical Engineering (top of class). I'm a Microsoft Certified Azure Data Scientist and have authored three published papers on state-of-the-art time-series forecasting.

Experience

Infinite Process Solutions

Lead R&D Software Engineer

Architect of MLOps & AI-based predictive maintenance modeling. Designed and deployed cloud infrastructure, data pipelines with Python & Airflow, and deep learning models with fast.ai & MLFlow.
Lead development of company products including predictive maintenance solutions, remote SCADA software, and inventory management systems.
Designed IoT hardware architecture to interface with cloud-based predictive maintenance solution.
WebApp development for company products using modern full-stack technologies.
Provide Siemens PLC and HMI maintenance and support for clients including WaterNet and Zeiss (3rd level software support - Germany).
Tools: Python, Azure ML, Airflow, fast.ai, MLFlow, Django, Docker, Siemens PLC/HMI

2023 - Present

Pliant

Software Engineer

Developed C# desktop applications for HMI systems using MVC-WPF pattern with Entity Framework for database logging and statistics.
Designed Power BI reports for fruit quality analysis, processing vast data sources for the Rijk Zwaan Paprika Fruit Quality Grading project.
Integrated AI models into production systems: implemented C++ DLL inference to detect defects using YOLO v6 trained models.
Modified PLC communication systems using TwinCAT ADS .NET and performed MVTec Halcon vision scripting.
Conducted data-driven research and proof-of-concept studies for new client projects.
Tools: C#, .NET, WPF, Entity Framework, TwinCAT ADS, Power BI, YOLOv6, MVTec Halcon

2022 | The Netherlands

Tomamate (Self-employed)

Software Controls Engineer

Designed Ignition HMI systems for multiple battery production lines at GM T1 Flex (Michigan), GM Oshawa, and DWFritz Battery Lines (Oregon).
Led PLC programming projects including architectural design, offline programming, and on-site commissioning for automotive and battery production facilities.
Created and improved control system software architectures, ensuring optimized functionality and resilient designs.
Led teams to roll out software updates and managed large-scale hardware setup, commissioning, and troubleshooting.
Ensured customer satisfaction during Factory Acceptance Test (FAT) checks and implemented system safety hardware design updates.
Tools: Ignition HMI, PLC Programming, Industrial Automation Systems

2021 - 2022 | USA and Canada

CIGNEX Datamatics

Project Trainee

Designed a library management system for a local library, where we undertook activities like requirement elicitation, preparing Data Flow and Entity-Relationship diagrams.
Delivered a solution for a POC involving Automatic Financial Document Classifier using Natural Language Processing and Support Vector Machines with 96% accuracy on the company’s data.
Tools: Python, Scikit-learn, NLTK

June 2017 - July 2017 | Ahmedabad, India

Projects

                
GPT Geenie
                  A complete SaaS WebApp product for deploying LLM-based chatbots
                
AccomplishmentsTools: Django, React.js, PostgreSQL, OpenAI API, Tailwind CSS
Full-stack web application for easy deployment of styled, LLM-based chatbots to any website.
Integrated OpenAI GPT models with custom prompting and styling options.
Built user-friendly interface for non-technical users to create and manage chatbots.
Deployed with production-ready architecture including database optimization and API rate limiting.

AI Predictive Maintenance
                  Cloud-based predictive maintenance solution for industrial equipment
                
                Accomplishments
                Tools: Python, Azure ML, fast.ai, MLFlow, Airflow, Docker
Designed and implemented MLOps pipeline for real-time sensor data processing.
Deployed ensemble deep learning models for equipment failure prediction.
Built IoT hardware interface for cloud-based data streaming.
Architected scalable infrastructure on Azure with automated data pipelines.

Industrial Control Systems
                  PLC programming and SCADA development for automotive production lines
                
                Accomplishments
                Tools: Siemens TIA Portal, Rockwell Studio 5000, Ignition SCADA, C#
Programmed and commissioned 100+ discrete and batch manufacturing lines globally.
Designed control system architectures for Ford, BMW, and GM automotive facilities.
Developed HMI/SCADA interfaces with real-time monitoring and data logging.
Integrated robotics, conveyors, and vision systems with PLC control logic.

Time-Series Forecasting Research
                  State-of-the-art hybrid and ensemble models for time-series prediction
                
                Accomplishments
                Tools: Python, TensorFlow, PyTorch, Scikit-learn, Statistical Models
Published 3 research papers on state-of-the-art time-series forecasting methods.
Developed hybrid models combining statistical and deep learning approaches.
Implemented ensemble techniques to improve prediction accuracy.
Achieved top-3 placements in multiple data science competitions.

Video Summarizer
                  A Seq2Seq model that generates a short summary of the given input video.
                
AccomplishmentsIncorporated CNN to detect and classify objects in the video frames and Long Short Term Memory for
                    generating a summary.
Evaluated the model on MSVD (Microsoft Video Description Corpus) dataset; achieved 0.77, 0.71,
                    0.52 scores respectively on ROGUE,
                    BLEU, METEOR evaluation metrics.

Image Generator
                  An image generator based on the concept of adversarial networks (GANs)
                
AccomplishmentsDeveloped system was tested on a human-face database and loss was calculated by comparing the PCAs
                    of generated and original image.
Calculated difference in PCA was less than 10%, depicting the successful generation of an image by
                    the generator.

Head Counting System
                  A system that calculates the attendance of the class from a panoramic image of a live classroom.
                
AccomplishmentsUsed Singular Value Decomposition for image compression; applied various image processing
                    techniques and morphological operations to
                    detect the number of heads.