About the Company is an omnichannel fashion & lifestyle destination that offers 1400+ fashion & beauty brands in the UAE, KSA, Kuwait, Oman, Bahrain & Qatar. Customers can shop the latest on-trend outfits, shoes, bags, beauty essentials and accessories from international brands such as Tommy Hilfiger, Calvin Klein, Hugo, Marks & Spencers, Dune London, Charles & Keith, Aldo, Crocs, Birkenstock, Skechers, Levi’s, Nike, Adidas, Loreal and Inglot amongst many more. recently opened GCC’s first phygital store at Dubai Hills Mall; an innovative tech-led space whichcombines the best of both online & offline shopping with online browsing & smart fitting rooms.OverviewThe ML Engineer will extract insights and build models that will drive key business decisions. The candidate will work closely with other data scientists, software engineers and product managers to design, build, optimize and deploy machine learning systems and solutions. This role is ideal for someone with a strong analytical mindset, a passion for data, and a desire to grow in a fast-paced e-commerce environment.Necessary Skills Python: Proficiency in python, with knowledge of popular libraries like pandas, numpy, scipy, scikit-learn, tensorflow, pytorchSQL: Strong ability to write and optimize complex SQL queries to extract and manipulate large datasets from relational databasesData Analysis & Visualization: Ability to work with large datasets and extract meaningful insights and able to leverage data visualization tools and librariesData Wrangling & Preprocessing: Expertise in cleaning and transforming raw data into structured formatsStatistical Analysis: A solid understanding of descriptive and inferential statistics, including hypothesis testing and probability theoryMachine Learning & Deep Learning: Familiarity with supervised and unsupervised learning algorithms such as regression, tree based methods, clustering, boosting and bagging methodologiesMachine learning workflows: feature engineering, model training, model optimization , validation and evaluationML Deployment: Deploying machine learning models to production environments, ensuring they meet the scalability, reliability, and performance requirementsDevOps: Git, CI/CD pipelines, dockerization, model versioning (mlflow), monitoring platformsCloud Platforms: Experience with cloud platforms like AWS, Google Cloud or Azure for deploying modelsProblem-Solving & Analytical Thinking: Ability to approach complex problems methodically and implement robust solutionsCollaboration & Communication: Strong ability to work with cross-functional teams and communicate technical concepts to non-technical stakeholders.Adaptability & Learning: Willingness to quickly learn new tools, technologies, and algorithmsAttention to Detail: Ability to carefully test and validate models, ensuring they work as intended in productionGood to have:Familiarity with big data technologies such as Spark or HadoopObject-oriented programming (OOP)Knowledge of data privacy and security practices when working with sensitive dataExperience working with big data tools (e.g., Apache Kafka, Apache Flink) for streaming data processingFamiliarity with feature stores like FeastExperience working with e-commerce dataResponsibilitiesDesign and implement machine learning models, algorithms, and systemsBuild and maintain end-to-end machine learning pipelines- model training, validation, and deploymentExperiment with different algorithms and approaches to optimize model performanceCollaborate with software engineers, product managers, analysts to build scalable, production-ready solutionsCommunicate complex technical concepts to non-technical stakeholdersStay updated with the latest advancements in machine learning and deep learning.Evaluate and experiment with new tools, libraries, and algorithms that could improve model performanceCollaborate on proof-of-concept (POC) projects to validate new approaches and techniquesBenefitsFull-time roleCompetitive salaryCompany employee discounts across all brandsMedical & health insuranceCollaborative work environmentGood vibes work cultureQualificationsBachelor's degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)At least 2 years' of experience in quantitative analytics or data modeling and developmentDeep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithmsFluency in a programming language (Python, C,C++, Java, SQL)
Job Title
Machine Learning Engineer