{"id":82459,"date":"2026-03-27T19:03:03","date_gmt":"2026-03-27T15:03:03","guid":{"rendered":"https:\/\/herecareers.com\/job\/data-scientist-mlops\/"},"modified":"2026-03-27T19:03:04","modified_gmt":"2026-03-27T15:03:04","slug":"data-scientist-mlops","status":"publish","type":"job_listing","link":"https:\/\/herecareers.com\/ar\/job\/data-scientist-mlops\/","title":{"rendered":"Data Scientist \u2013 MLOps"},"content":{"rendered":"<p>411_3340846<\/p>\n<p><h3>Overview <\/h3>\n<p><b>VAM Systems <\/b> is currently looking for <b>Data Scientist \u2013 MLOps <\/b> for our <b>UAE <\/b> operations with the following skillsets &#038; terms and conditions: <\/p>\n<h3>Qualifications <\/h3>\n<ul>\n<li>Bachelor\u2019s degree in Computer Science, Data Science, Engineering, or a related field. <\/li>\n<li>Master\u2019s degree or certifications in ML\/AI\/MLOps are an advantage. <\/li>\n<\/ul>\n<h3>\u0627\u0644\u062e\u0628\u0631\u0629 <\/h3>\n<ul>\n<li>3-4 years of hands-on experience as a Data Scientist or ML Engineer with strong focus on model deployment. <\/li>\n<li>Proven experience deploying ML, DL, and GenAI models in production environments. <\/li>\n<li>Practical experience working with MLOps workflows, including model training, versioning, deployment, monitoring, and automation. <\/li>\n<\/ul>\n<h3>Skills <\/h3>\n<ul>\n<li>Strong Python programming skills (Pandas, NumPy, Scikit-learn). <\/li>\n<li>Proficiency in ML frameworks: TensorFlow, PyTorch, MLflow, Hugging Face. <\/li>\n<li>Deep understanding of MLOps tooling: MLflow, Airflow, Kubeflow, Docker, Kubernetes, Azure ML. <\/li>\n<li>Experience with CI\/CD (GitHub Actions, Azure DevOps). <\/li>\n<li>Ability to build APIs (FastAPI, Flask) and containerized deployments. <\/li>\n<li>Experience with LLMs, RAG pipelines, vector databases (FAISS, Pinecone), and prompt engineering. <\/li>\n<\/ul>\n<h3>\u0627\u0644\u0645\u0633\u0624\u0648\u0644\u064a\u0627\u062a <\/h3>\n<p><b>Data Science &#038; Analytics: <\/b> <\/p>\n<ul>\n<li>Develop Design and develop data science solutions using traditional ML and modern modeling techniques. <\/li>\n<li>Perform exploratory data analysis (EDA), feature engineering, and data preprocessing for model development. <\/li>\n<li>Define measurable success metrics, including accuracy, precision, recall, throughput, and latency. <\/li>\n<\/ul>\n<p><b>Machine Learning Model Development: <\/b> <\/p>\n<ul>\n<li>Contribute Build, test, and validate supervised and unsupervised ML models using best practice methodologies. <\/li>\n<li>Evaluate multiple algorithms and optimize hyperparameters to improve model robustness. <\/li>\n<li>Maintain documentation and ensure model interpretability where applicable. <\/li>\n<\/ul>\n<p><b>MLOps &#8211; End to End Model Deployment: <\/b> <\/p>\n<ul>\n<li>Implement Lead deployment of ML\/AI models into production using CI\/CD, automation, and containerized workflows. <\/li>\n<li>Develop reproducible ML pipelines for training, testing, serving, and monitoring. <\/li>\n<li>Implement scalable APIs and microservices for model inference. <\/li>\n<li>Set up real time and batch inference systems ensuring reliability and uptime. <\/li>\n<li>Detect and respond to model drift, data drift, and performance degradation. <\/li>\n<\/ul>\n<p><b>Generative AI \/ LLMs Deployment <\/b> <\/p>\n<ul>\n<li>Deploy LLM-powered applications, including prompt based models, fine tuned models, and RAG systems. <\/li>\n<li>Build scalable back end infrastructure for hosting LLMs using Azure OpenAI, Hugging Face, or equivalent platforms. <\/li>\n<li>Evaluate LLM outputs for accuracy, safety, and consistency, enforcing enterprise guidelines. <\/li>\n<\/ul>\n<p><b>Microsoft Automation &#038; Engineering <\/b> <\/p>\n<ul>\n<li>Develop automation scripts (Python\/CLI) to optimize data pipelines, monitoring, alerts, and deployment workflows. <\/li>\n<li>Work with APIs, microservices, and event driven architectures to support ML deployments. <\/li>\n<\/ul>\n<h3>\u0627\u0644\u0623\u062d\u0643\u0627\u0645 \u0648\u0627\u0644\u0634\u0631\u0648\u0637 <\/h3>\n<p><b>Joining time frame: <\/b> maximum 4 weeks <\/p>\n<p>The selected candidates shall join VAM Systems &#8211; UAE and shall be deputed to one of the leading organizations in UAE. <\/p>\n<\/p>\n<p> #J-18808-Ljbffr<\/p>\n<p>2026-03-03 08:35:49<\/p>","protected":false},"author":100,"featured_media":0,"comment_status":"open","ping_status":"open","template":"","job_listing_type":[68],"job_listing_category":[1348],"job_listing_location":[720],"job_listing_tag":[],"class_list":["post-82459","job_listing","type-job_listing","status-publish","hentry","job_listing_type-full-time","job_listing_category-it-technology","job_listing_location-united-arab-emirates"],"metas":{"_job_featured_image":"","_job_featured":"","_job_filled":"","_job_urgent":"","_job_category":{"1348":"IT &amp; 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