AI Application Developer

at  Mitie

YOUR QUALIFICATIONS & EXPERIENCE:

• Software development background, especially in open-source technologies like .Net, NodeJS, REACT, Angular and others; Experience and drive to do “full-stack” development
• Experience in integrating ML models into existing and new applications
• Demonstrable deep experience with developing and deploying AI, Machine Learning and Data solutions.
• Experience with supervised and unsupervised learning algorithms (e.g., linear regression, decision trees, neural networks), from MLOps point of view
• Experience with programming languages for AI development (e.g., Python, R, TensorFlow, PyTorch), from MLOps point of view
• Experience working with large datasets and data preparation techniques.
• Strong understanding of cloud platforms for AI development (Azure preferred).
• Experience with version control systems (e.g., Git).
• Excellent problem-solving and analytical skills.
• Strong critical thinking and ability to identify patterns in data.
• Proficient in software development best practices (e.g., Agile methodology, unit testing).
• Effective communication and collaboration skills to work with cross-functional teams.
• Ability to learn new technologies and adapt to changing environments.
• Excellent written and verbal communication skill

OBJECTIVES AND RESPONSIBILITIES

This is a unique opportunity to play a pivotal implementation role in shaping the future of the Mitie Facility Management built environment. You will be part of Mitie IS DevOps team and will work with Mitie teams to implement AI-powered solutions that improve efficiency, sustainability, and occupant wellbeing across Mitie client portfolio. You will work closely with a cross-functional team of engineers, data scientists, designers, and business stakeholders to bring the Mitie AI strategy to life.

KEY RESPONSIBILITIES:

• Implement MLOps pipelines: Establish and manage complete MLOps workflows, including continuous integration, delivery, and deployment of AI/ML models in production environments.
• Optimise models for efficiency, scalability, and resource utilization.
• Develop and implement model testing and evaluation frameworks.
• Deploy and monitor models in production environment, ensuring continuous performance and reliability.
• Integrate AI into existing products and services
• Collaborate effectively with cross-functional teams (data scientists, software engineers, product managers) to ensure successful AI adoption.
• Stay current with the latest advancements in AI technology and best practices, continuously improving your skills and knowledge.
• Promote ethical and responsible use of AI by adhering to company policies and industry standards
• Manage and maintain AI infrastructure and platforms.
• Develop and implement data pipelines for model training and inference. · Develop/ enhance new and existing applications integrating the AI capabilities and ML models built by the insight team.