Principal AI Engineer

at  Reach Digital Health

JOB OVERVIEW

As a Principal AI Engineer within our Engineering team, you will be a key innovator, applying cutting-edge artificial intelligence and machine learning methodologies to augment and amplify the impact of our Data Science team. You will collaborate closely with other Data Scientists and teams to create scalable, reliable AI/ML solutions that address complex challenges in health and policy. Your work will focus on pushing the boundaries of what’s possible with AI/ML, mentoring and training team members, and promoting ethical and responsible use of AI/ML in the organisation.

QUALIFICATIONS

• 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.

SKILLS AND EXPERIENCE REQUIRED

• 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.

• 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.