<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <strong>Company Description<br/><br/></strong>Welcome to Kanadevia Inova, a global innovation leader in the waste infrastructure space, where we believe in creating a sustainable future through technology and innovation.<br/><br/><strong>Transforming Waste into Value<br/><br/></strong>At Kanadevia Inova, we pride ourselves on being at the forefront of waste-to-X technology. We are not just waste managers; we are creators of value from what communities discard. Your role at Kanadevia Inova directly contributes to turning something once considered useless - waste - into something invaluable: energy, heat, hydrogen, fertilizer, and beyond.<br/><br/><strong>Job Description<br/><br/></strong><ul><li>Industrialise and operate AI/ML solutions by transforming prototypes into scalable, production-ready applications.</li><li>Design, implement, and maintain end-to-end MLOps pipelines covering training, validation, deployment, monitoring, and retraining.</li><li>Collaborate closely with Data Scientists, Data Engineers, Software Engineers, Product Managers, and business stakeholders to deliver AI solutions.</li><li>Ensure reliability, security, compliance, data integrity, performance, and governance throughout the machine learning lifecycle.</li><li>Monitor and optimise model performance, troubleshoot production issues, and support continuous improvement while mentoring less experienced colleagues.<br/><br/></li></ul><strong>Qualifications<br/><br/></strong><ul><li>MSc in Computer Science or a STEM field with a strong computer science focus, plus experience working in agile software development environments.</li><li>Strong Python programming skills and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.</li><li>Solid understanding of MLOps practices, including model deployment, versioning, monitoring, and lifecycle management in production environments.</li><li>Experience with cloud platforms (preferably Azure), containerisation technologies (Docker), APIs, databases, and distributed systems.</li><li>Knowledge of data engineering and data processing frameworks; experience with industrial IoT, time-series data, computer vision, or Physics-AI solutions is advantageous.<br/><br/></li></ul><strong>Additional Information<br/><br/></strong>For HR agencies: Please note that we do not accept applications coming from agencies. Thank you. </div>