Principal AI Engineer

Responsibilities

• Design, develop, and deploy AI/ML models in collaboration with other Data Scientists in areas such as:
  • Predictive modelling for early identification of health and behaviour risks.
  • Recommendations for delivering personalised content and suggestions to users.
  • Natural language processing for analysing qualitative data.
  • Anomaly detection for identifying patterns and trends in large datasets.
• Contribute to the design and development of high-impact AI/ML models that address critical organisational challenges and opportunities.
• Contribute to the end-to-end MLOps lifecycle, from model development to deployment, monitoring, and maintenance.
• Provide strategic guidance on AI/ML best practices, ensuring models are built with scalability, security, and ethical considerations in mind.
• Lead efforts in mentoring and developing the AI/ML capabilities of other Data Scientists, fostering a culture of continuous learning and improvement.
• Champion the implementation of ethical AI practices, ensuring that models adhere to principles of fairness, accountability, and transparency.
• Evaluate and mitigate potential risks associated with AI/ML models.
• Monitor and evaluate the performance and impact of AI/ML models.
• Provide training and support to other Data Scientists on the use and interpretation of AI/ML tools and results.
• Stay abreast of the latest advancements in AI research and advocate for their responsible and ethical adoption.

Skillset

• Master’s or Ph.D. in a relevant field (e.g., Computer Science, Artificial Intelligence, Machine Learning).
• 5+ years of experience in applied AI research and development, with significant experience in MLOps and operationalising machine learning models in production environments.
• Strong expertise in machine learning frameworks and programming languages (e.g. Python).
• Deep experience with MLOps practices and tools, including CI/CD pipelines, model versioning, and automated deployment.
• Proven track record of leading AI/ML projects from conception to production at scale.
• Experience with a range of AI/ML techniques, including deep learning, reinforcement learning, natural language processing, and transformer models.
• Demonstrated experience in designing and implementing ethical AI practices, with a strong understanding of fairness, accountability, and transparency in AI.
• Ability to evaluate the potential risks and consequences of AI/ML models, particularly in sensitive projects, and implement safeguards to mitigate these risks.
• Demonstrated experience in mentoring, training, and knowledge sharing within technical teams.
• Proven ability to collaborate effectively with cross-functional teams.
• Excellent communication and presentation skills, both written and verbal.
• Passion for social impact and a commitment to ethical AI development.