Pioneering trusted medical solutions to improve the lives we touch: Convatec is a global medical products and technologies company, focused on solutions for the management of chronic conditions, with leading positions in advanced wound care, ostomy care, continence care, and infusion care. With around 10,000 colleagues, we provide our products and services in almost 100 countries, united by a promise to be forever caring. Our solutions provide a range of benefits, from infection prevention and protection of at-risk skin, to improved patient outcomes and reduced care costs. Group revenues in 2022 were over $2 billion. The company is a constituent of the FTSE 100 Index (LSE:CTEC). Job Summary If you are looking to join a small, driven, and growing team where you can leverage your software engineering experience to build highly impactful digital solutions that impacts the lives of our patients and healthcare providers, then this is the position for you. You will be the Senior AI-Machine Learning Engineer (MLOps) within the team. You will be responsible for working within project teams and ensuring the solution architecture creates delightful experience for internal and external stakeholders. Key Duties and Responsibilities • Partner closely with data scientists, and data engineers, and other technical teams to implement and optimize production grade MLOps systems. • Strong engineering fundamentals in software design, version control, continuous integration and delivery, testing, containers, and orchestration, monitoring and logging for enterprise-grade machine learning platforms in real world environments. • Implement model monitoring, orchestration, model re-training, version control, continuous integration, and delivery. • Build awareness, increase knowledge, and drive adoption of MLOps technologies and architecture patterns, sharing customer and engineering benefits to gain buy-in (working closely with leaders, other SMEs, and engineers) • Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization • Be part of a high-performing team developing and implementing AI algorithms to help address solve complex problems and create unique solutions in healthcare. • Build awareness, increase knowledge, and drive adoption of MLOps technologies and architecture patterns, sharing customer and engineering benefits to gain buy-in (working closely with leaders, other SMEs, and engineers) • Carryout architecture reviews and enabling teams fix issues that arise from the reviews. • Ability to effectively communicate, influence and drive consensus between the business, technology teams, and executive leadership in an organization with multiple lines of business. • Responsible for working in an Agile environment and evaluating pre-project ideas in terms of technical complexity and solution architecture. Participates in high-level estimation. About You • Bachelor’s degree in computer science, AI, Data Science, Software or Computer Engineering, Computational Statistics, Mathematics, or a closely related discipline. Master’s or above is highly preferred. • Experience working in a regulated industry, or the medical device space is highly preferred. • 5 years of experience as a MLOps engineer (AI-ML). • Demonstrable experience in using cloud based MLOps platform including AWS and / or Databricks. • AWS Tools include AWS code build, code commit, code pipeline, ECR, S3, Sagemaker registry / container, AWS CloudFormation, step functions, and AWS lambda. • Databricks, development, staging, production areas, bronze, silver and gold tables, MLflow, lakehouse monitoring, and model retraining. • Use of Terraform to build cloud-based infrastructure is also desirable. • Good knowledge of MLOPs life cycle including data preparation, model build, validate, test, deploy and monitor and retrain. • Demonstrable expertise using scripting such as Python. • Good software skills to support models through the life cycle, namely: pipelines and models from development, staging, UAT to production. Adherence to coding standards, configuration control and continuous integration and delivery. Working Conditions This position will be mainly remote; however, we will expect our successful candidate to travel for team meetings to either our Paddington or Deeside site (approx. once per month). Travel Position may involve travel up to 10% of the time, mostly within UK/US but overseas travel is expected. Most trips will include overnight travel.