Senior Computer Vision & MLOps Engineer

Protex AI’s Site Intelligence platform shows industrial businesses what’s actually happening across their operations. It connects cameras, enterprise systems and operational knowledge. Computer vision turns camera footage into live operational data, and AI agents use that data to explain performance, flag what needs attention and route the fix to the right team. Our customers are some of the world’s largest manufacturing, logistics and warehousing companies, including PepsiCo, FedEx and General Motors. We work with senior Safety and Operations leaders, giving them the visibility to run smarter, safer sites. Protex AI raised an oversubscribed $36 million Series B led by Hedosophia, with participation from Salesforce Ventures and existing investors. Our team includes people who previously held senior roles at AWS, Microsoft and Google. In-Office Expectation: Hybrid – 2 days/week in-office Employment Type : Full-time (Direct Hire) Please note that this is not an open position for contractors or remote work. About the Team The Computer Vision Operations team owns the machine learning lifecycle behind every Protex detection. We build and run the pipelines that turn video from client sites into curated datasets, train and evaluate our detection models, and optimise and release them to edge devices deployed around the world. Our current focus is delivering reliable detections to both the existing Safety product of Protex and the rapidly expanding new Operations product. What You’ll Do You will work with other experienced engineers driving continuous improvement of the machine learning lifecycle behind Protex AI's detections: the data and training pipelines, model evaluation and release, and monitoring in production. This is a hands-on individual contributor role. Your influence comes from leading high-impact work across teams, setting the technical standards others build on, championing client needs in technical discussions, and helping the engineers around you grow. You understand both the product and the technical aspects, and can drive key initiatives to fulfill both. You will: Shape the work before it is built: partner with product managers in scoping, design and drive the implementation. Set the technical direction for our ML platform. You continuously learn about the latest trends in computer vision and can balance those with the real-world constraints on compute, storage and costs. Lead triage and root-cause analysis on the team's support rotation when detection quality drops at a client site. You build components, tools and processes in a way that prevents issues in production and makes them faster to detect and faster to fix. Raise the engineering bar: review code as the quality gate, define standards for testing and reproducibility. Mentor and unblock other engineers through pairing, reviews and enablement sessions. Act as the technical voice of computer vision with product, infrastructure, application development, the install team, technical support and external partners. Make key contributions to the computer vision strategy. Model our core values: urgency, excellence, agency and care. What You’ll Need Bsc in Computer Science, Engineering or other relevant STEM 5+ years of software or ML engineering experience, including hands-on work on computer vision or machine learning systems in production. Hands-on experience with deep learning for computer vision, from training to deploying optimised models (e.g. PyTorch, TensorRT, ONNX). Strong Python skills, and experience building data, training or deployment pipelines on cloud infrastructure (AWS preferred), with containers and infrastructure as code. A solid grasp of model evaluation and MLOps A track record of owning architectural components, leading architecture discussions and driving complex technical projects across teams from design to production, without formal authority. Experience debugging production issues end to end Experience driving best practices in testing, reproducibility and code review, and mentoring other engineers. Product sense and clear communication: you connect model quality to client outcomes, write clear design docs, and translate strategic goals into actionable engineering plans. Nice To Have Experience scaling software systems in a startup or high-growth environment. Experience with video analytics or edge deployment. Experience with vision-language or foundation models. Experience with dataset curation, annotation workflows or labelling partners. Experience using AI coding agents in day-to-day engineering work. Exposure to data governance practices. Protex AI is an inclusive and equal opportunities employer. We are committed to creating an equitable workplace for everyone regardless of gender, civil status, family status, sexual orientation, religion, age, disability, education level, or race.