{"id":1654509,"url":"https://alion.io/job/eram-talent-associate-data-scientist-saudi-arabia","title":"Associate Data Scientist (Saudi Arabia)","company":{"id":6798,"name":"Eram Talent","domain":"eramtalent.com","url":"https://alion.io/company/eram-talent","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"C","score":59,"open_postings":433,"ghost_share":0.679,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Dhahran, Saudi Arabia","Riyadh, Saudi Arabia","Jubail, Saudi Arabia","Dammam, Saudi Arabia","Khobar, Saudi Arabia"],"countries":["SA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ArgoCD","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"HPC","optional":false},{"name":"Hugging Face","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"NVIDIA NIM","optional":false},{"name":"OpenShift","optional":false},{"name":"Python","optional":false},{"name":"SLURM","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-01T00:00:00Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-30T12:29:04Z","board_verified":true,"closed_at":null,"days_open":29,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":28},"description":"We are looking for an experienced Associate Data Scientist with strong expertise in Artificial Intelligence (AI), Machine Learning (ML), Generative AI (GenAI), and Large Language Models (LLMs). The ideal candidate should have hands-on experience in AI model development, deployment, cloud infrastructure, distributed computing, and MLOps/LLMOps to support scalable, high-performance AI applications.\nKey Responsibilities\nDevelop, train, test, evaluate, and deploy AI/ML models and Generative AI applications.\n\nDesign, implement, and optimize LLM-based solutions, including inference mechanisms and performance tuning.\n\nBuild and manage scalable AI infrastructure using GCP, OpenShift, Kubernetes, and Docker.\n\nImplement MLOps and LLMOps pipelines to automate model development, deployment, monitoring, and maintenance.\n\nOptimize LLM inference performance through distributed computing, inference benchmarking, and scaling strategies to meet SLAs/SLOs.\n\nManage GPU-based workloads, distributed processing, and autoscaling for AI applications.\n\nWork with NVIDIA NIM, Hugging Face, and NVIDIA SuperPOD environments, including HPC, Slurm, and Kubernetes.\n\nDevelop AI application architectures and manage end-to-end AI workflows.\n\nImplement monitoring, dashboards, and performance tracking for ML/LLM workloads and applications.\n\nEstablish and maintain CI/CD pipelines using tools such as Argo CD, Git, and Jenkins.\n\nCollaborate with cross-functional teams, manage project activities, and ensure the delivery of scalable AI solutions.\n\nRequirements\nBachelor's degree in Computer Science or a related field.\n\nMore than 5 years of relevant professional experience in Data Science, AI, Machine Learning, or related fields.\n\nStrong programming skills in Python and SQL.\n\nHands-on experience with cloud technologies such as GCP, OpenShift, Kubernetes, and Docker.\n\nStrong understanding of AI/ML model training, testing, evaluation, and deployment.\n\nPractical knowledge of MLOps, LLMOps, LLMs, and Generative AI.\n\nUnderstanding of LLM architecture, inference mechanics, and performance optimization.\n\nExperience in inference scaling, distributed computing, benchmarking, and GPU-based workloads.\n\nFamiliarity with NVIDIA NIM, Hugging Face, and NVIDIA SuperPOD environments.\n\nExperience with monitoring, dashboards, AI application architecture, and end-to-end workflows.\n\nKnowledge of DevOps practices and CI/CD tools, including Argo CD, Git, and Jenkins.\n\nExcellent communication, professionalism, leadership, and project management skills.\n\nPreferred Skills\nExperience working with large-scale AI infrastructure and distributed AI workloads.\n\nStrong analytical and problem-solving abilities.\n\nEffective communication, teamwork, and stakeholder management skills.\n\nAbility to lead project activities and collaborate across technical 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