We are seeking a highly skilled and innovative Artificial Intelligence and Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing developing and deploying AI and ML models that drive impactful solutions across various domains including education data analytics automation and smart systems. You will work alongside interdisciplinary teams to integrate cuttingedge technologies into practical applications transforming data into intelligent action.
Key Responsibilities:
- Model Development & Deployment
- Design train evaluate and deploy machine learning and deep learning models
- Build and maintain scalable AI solutions for realtime or batch processing systems.
- Optimise model performance including accuracy latency and resource consumption.
- Data Engineering & Processing
- Collaborate with data engineers and analysts to source clean and transform data.
- Apply advanced statistical and data mining techniques to extract meaningful patterns.
- Research & Innovation
- Stay updated with the latest advancements in AI and ML technologies.
- Prototype innovative solutions contribute to research publications and recommend adoption of new frameworks.
- Systems Integration
- Develop APIs and services to integrate AI solutions into existing platforms or applications.
- Collaborate with software engineers and DevOps teams to ensure productionlevel stability.
- Collaboration & Communication
- Work closely with academic and operational teams to understand business needs and translate them into technical solutions.
- Prepare documentation reports and presentation materials to communicate findings and methodologies.
Requirements
Required Qualifications:
Bachelors degree in Computer Science Artificial Intelligence Data Science Engineering or related field (Master s or PhD preferred).
Minimum 3 years of handson experience in AI/ML engineering or data science roles.
Proficient in Python and common ML libraries (e.g. TensorFlow PyTorch scikitlearn Keras).
Strong understanding of machine learning algorithms neural networks natural language processing (NLP) and computer vision.
Experience in model deployment using cloud platforms (e.g. AWS Azure GCP) or containerised environments (Docker Kubernetes).
Desirable Skills:
Knowledge of MLOps tools and CI/CD pipelines for ML projects.
Familiarity with big data platforms (e.g. Spark Hadoop).
Experience with academic or educational systems (LMS AI in education) is a plus.
Demonstrated contributions to opensource projects research publications or hackathons.