The Directed Energy Research Center of the Technology Innovation Institute is looking for an AI Engineer to work as part of the Signals, Electronics, and Acoustics team.
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Technology Innovation Institute (TII) is a publicly funded research institute based in Abu Dhabi, United Arab Emirates. It is home to a diverse community of leading scientists, engineers, mathematicians, and researchers from across the globe, transforming problems and roadblocks into pioneering research and technology prototypes that help move society ahead.
Responsibilities
- Develop and deploy machine learning models for anomaly detection applications, focusing on real-time monitoring systems and advanced pattern recognition algorithms using modern deep learning frameworks and cloud-based infrastructure.
- Design, develop, and optimize ML models for anomaly detection on time series, sensor, and visual data.
- Work closely with the sensor development engineering team to ensure the sensor design helps the ML model performance.
- Implement and maintain deep learning architectures for real-time anomaly detection.
- Work with engineers to integrate models into production systems that scale.
- Optimize model performance for edge and resource-constrained deployments.
- Document model architectures, training procedures, and deployment guidelines for knowledge transfer.
Requirements
- Strong hands-on experience with ML/DL frameworks (PyTorch preferred).
- Strong programming skills in Python.
- Experience with anomaly detection techniques (autoencoders, clustering, semi-supervised methods).
- Experience deploying and running ML workloads on AWS.
- Technical expertise in computer vision for anomaly detection in images, audio, or RF.
- Experience with unsupervised and semi-supervised learning for unlabeled datasets.
- Experience in building or maintaining a dataset.
- Bachelor’s or Master’s in AI, Data Science, Computer Science, Statistics, or a related field.
- 3+ years of hands-on experience building and deploying ML models.
- Proven track record of implementing anomaly detection systems for real-world applications.
- Digital signal processing experience preferred.
- Strong problem-solving skills with the ability to work independently and in a team.
- Effective communication and collaboration skills across teams.
