Job Description

Overview

About AIQ

AIQ is a joint venture company between ADNOC and Group 42, which focuses on developing artificial intelligence technologies in the United Arab Emirates. AIQ develops and commercializes AI products and applications for the oil and gas industry. 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.

About The Role

We are looking for new team members to join our data science team. 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. All in all, being a Data-Scientist at AIQ gives the unique opportunity to contribute to the development of complete AI solutions going through all the following key steps: technical formalization of the business needs, database creation (QC, selection and labeling), data preprocessing, algorithms development and implementation, model performance evaluation, deployment in production and even continual learning of AI machines.

Responsibilities

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 3 years of experience demonstrating depth and breadth in computer vision tasks (classification, segmentation, detection, pose estimation) with CV approaches, state-of-the-art machine-learning, deep-learning, or other AI technologies; * Demonstrated experience in developing core AI algorithms in industry, industrial AI or for real-world AI problems; * Demonstrated relevant experience in implementing robust and scalable industrial AI solutions; * 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 prefered) and all 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. * Ability to manage ambiguity, take initiative, and hit the ground running. * Results-driven and proactive personality;

Educational requirements:

* Master's degree or or Ph.D. in Computer Science, Applied Mathematics, Statistics, or any AI-related field;