AI Engineer

• Deliver end-to-end AI solutions by designing, training, and deploying Machine Learning models and AI systems
• Collaborate with cross-functional teams including backend/frontend engineers, product managers and contribute to architectural decisions.
• Preprocess and analyse large datasets from structured and unstructured sources.
• Develop data pipelines and model training infrastructure.
• Optimize model performance and scalability in production environments.
• Implement CI/CD workflows for model versioning and deployment.
• Assess and apply adoption of low-/no-code platforms like Copilot Studio to accelerate AI solution delivery and integrate with existing ML systems.
• Understand cloud-native architecture concepts and have knowledge of best practices for high availability, scalability, resilience, performance, and security requirements in the cloud.
• Stay current with industry trends and academic research to integrate state-of-the-art techniques.
• Ensure compliance with data security, data privacy regulations and ethical AI practices.

• Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related fields
• 2-5+ years of experience in AI/ML engineering or applied machine learning.
• Proficiency in Python, with knowledge of ML libraries
• Experience with deep learning frameworks (e.g. TensorFlow)
• Strong knowledge of data structures, algorithms, and software engineering principles.
• Experience with cloud platforms (Azure, AWS) and ML ops tools (e.g. Azure Machine Learning, MLflow)
• Familiarity with containerization and orchestration (Docker, Kubernetes)
• Proficiency in RESTful API development and strong understanding of SQL and relational database design.
• Demonstrated problem-solving ability, with a proactive mindset and eagerness to continuously learn new technologies
• Knowledge of regulatory and security considerations when delivering AI-enabled digital services
• Effective communication skills, able to explain technical concepts to non-technical stakeholders.
• Collaborative mindset and willingness to mentor or guide team members

Desirable experience & skills

• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Experience in end-to-end AI solution lifecycle: problem definition, data collection, model development, deployment, and monitoring.
• Work on scalable AI/ML projects across company functions and technical domains such as NLP, computer vision, predictive analytics, or recommendation systems.
• Contributions to open-source AI projects or research publications.
• Experienced in AI/ML strategy, technology selection, and model governance standards.
• Experienced in Agile development cycles and DevOps practices