Overview:
About AIQ:
AIQ is an Abu Dhabi based joint venture company between Presight and ADNOC, which focuses on developing artificial intelligence technologies. AIQ develops and commercializes AI products and applications for energy world. It aims in providing end-to-end solutions by using its data, cloud and talents to develop AI solutions that seek to reduce costs and generate revenue for its clients. AIQ embodies an innovative and entrepreneurial spirit that embraces challenges to push boundaries and seeks to welcome professionals to its team that share the desire to make meaningful and impactful contributions to its mission. Always on the cutting edge of technology, AIQ provides its talent all the opportunities to thrive and excel. Working at AIQ includes dealing with massive data sets, an AI infrastructure that is powered by the latest NVIDIA GPU cloud computing platform and access to limitless computing, storage and network resources.
About the role:
We are seeking a Senior Data Scientist (Computer Vision) to join our team operating in the Oil and Gas sector, specifically in upstream production modeling and optimization. You will work closely with cross-functional teams to analyze data, implement, deploy and maintain solution, and deliver actionable recommendations to improve production management and maximize operational performance.
Responsibilities:
Develop next generation AI-enabled software products for oil & gas industry;
Formalize Oil & Gas problems into AI problems;
Translate business objectives into actionable analyses and insights;
Contribute to the solution design, in collaboration with other data scientists, engineers and SMEs;
Data preparation: Extract, clean, audit and preprocess data for analysis;
Data QC: Analyze quality of data produced and proactively develop solutions to data quality issues;
Contribute to the creation of large-scale labeled databases leveraging our annotation team;
Develop data-driven algorithms and prototypes for regression, classification, segmentation, anomaly detection, failure prediction and optimization;
Evaluate proposed AI solutions with respect to the project objectives;
Keep up to date with the latest technology trends;
Apply state-of-the-art AI techniques to improve existing solutions;
Deploy and maintain AI models in production;
Help prepare and visualize interim and final results of analyses;
Communicate ideas, plans, and results, effectively via oral presentations and written reports.Qualifications:
Required experience:
At least 5 years of experience in application of DL and ML techniques for various computer vision tasks (classification, segmentation, detection, pose estimation).
In depth knowledge on deep learning basics and architectures (Resnet, Inception, Unet, Yolo etc. for tasks mentione above) used in computer vision and their application is a must.
Demonstrated experience in developing core AI algorithms in industry, industrial AI or for real-world AI problems.
Experience of participation and winning in computer vision hackathons and competitions is a significant advantage.
Experience of working with CCTV (cameras networks) streams is a plus.
Experience in the oil & gas exploration & production company or oil field services company is a plus.
Required key skills:
Strong background in applied mathematics, algorithms and coding;
Proficient in machine-learning and/or deep-learning;
Strong background in AI application to signal-processing problems;
Proficient in Python development language
Strong skills and experience with classic CV tools (openCV), deep-learning frameworks (Pytorch) and popular machine-learning libraries (e.g., Scikit-learn);
Theoretical and practical knowledge of popular machine-learning algorithms (PCA, KNN, RandomForest, XGBoost, etc.) and deep-learning networks (CNNs, GANs, Diffusions, Transformers, etc.);
Hands-on with useful development tools (PyCharm, Jupyter, MLFlow, Git, Docker, etc);
Ability to build AI models and to find impactful and actionable recommendations based on the model;
Excellent communication, verbal and written skills;
Results-driven and proactive personality.
Educational requirements:
Masters degree or or Ph.D. in Computer Science, Applied Mathematics, Statistics, or any AI-related field.
