{"id":531912,"url":"https://alion.io/job/arcelormittal-senior-data-scientist-machine-learning-engineer","title":"Senior Data Scientist / Machine Learning Engineer","company":{"id":13461,"name":"ArcelorMittal","domain":"arcelormittal.com","url":"https://alion.io/company/arcelormittal","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":87,"open_postings":180,"ghost_share":0,"stale_share":0.739,"repost_share":0,"time_to_fill_p50_days":8,"computed_at":"2026-11-02T06:13:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Luxembourg City, Luxembourg"],"countries":["LU"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":93000,"max_usd":243000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2365},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Computer Vision","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false}],"status":"live","first_seen_at":"2026-02-05T00:00:00Z","employer_posted_date":"2026-02-05","last_verified_at":"2026-11-02T15:53:28Z","board_verified":true,"closed_at":null,"days_open":270,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":270},"description":"About ArcelorMittal Global Solutions AI Team\nThe ArcelorMittal Global Solutions AI Team is a transversal Artificial Intelligence capability enabling business divisions to create measurable value through responsible, production-grade AI and data solutions. We support the full lifecycle of AI initiatives across Finance, HR, Supply Chain, Logistics, Manufacturing, and Operations, while owning technical delivery, quality, and risk controls.\nOur portfolio includes document automation, forecasting, optimization, computer vision, predictive maintenance, AI-powered assistants, and GenAI-driven enterprise applications.\nRole Summary\nAs a Senior Data Scientist / Machine Learning Engineer, you will design, build, and operate end-to-end AI and machine learning solutions for the AMGS AI Team.\nIn the initial phase, you will work hands-on, primarily on Microsoft Azure, performing data analysis, training ML/DL models, and building AI applications, including LLM-powered solutions. As the team grows, you will progressively lead and mentor other data scientists and ML engineers, oversee their work, and ensure high standards of technical quality, robustness, and delivery across AI solutions.\nWhile Azure will be the primary platform, you are expected to expand into AWS over time as AMGS AI solutions evolve.\nKey Responsibilities\nHands-on AI / ML Development (Initial Phase)\nAnalyze structured and unstructured data to extract insights and define AI use cases\nDesign, train, evaluate, and improve ML and DL models\nBuild AI solutions across domains such as NLP, computer vision, forecasting, and optimization\nDesign and implement GenAI solutions using API-based LLMs (e.g. RAG, agents)\nDecide on the most appropriate approach (LLMs, classical ML, DL, or hybrid) based on the problem\nDevelop production-ready AI components and services\nAI Engineering & Platform Enablement\nIntegrate AI models and LLM-based components into applications and workflows\nCollaborate with software developers and cloud engineers on deployment and integration\nSupport monitoring, evaluation, and continuous improvement of AI systems\nContribute to AI architecture, best practices, and reusable components\nTechnical Leadership (As Team Grows)\nGuide and mentor other data scientists and ML engineers\nReview code, models, and solution designs\nDefine and enforce standards for data science, ML engineering, and GenAI development\nEnsure development quality, robustness, and maintainability of AI solutions\nCross-Functional Collaboration\nWork closely with business analysts, software developers, cloud engineers, and domain experts\nTranslate business problems into measurable AI and data solutions\nSupport adoption and change management for AI-driven applications\nRequired Skills & Experience\nAI / ML Expertise\nStrong experience in data science and machine learning in production environments\nDeep expertise in at least one ML domain (e.g. NLP, Computer Vision, Forecasting)\nBroad understanding of other ML domains and techniques\nStrong Python programming skills\nExperience training, evaluating, and improving ML/DL models\nGenAI & Modern AI Patterns\nHands-on experience with LLM-based applications\nUp-to-date knowledge of modern GenAI patterns (e.g. RAG, agents, prompt design)\nAbility to assess limitations, risks, and trade-offs of GenAI approaches\nCloud & Engineering\nExperience developing AI solutions on Azure\nAbility and willingness to work with AWS as needed\nSolid software engineering fundamentals (modularity, testing, version control)\nAbility to work independently and own AI solutions end-to-end\nProfessional Experience\nProven experience delivering AI/ML solutions in real-world projects\nExperience working in cross-functional teams\nExperience in complex or enterprise environments\nNice to Have\nExperience with MLOps practices and tooling\nExperience deploying and monitoring ML models in production\nExperience building AI-powered APIs or services\nFamiliarity with responsible AI, explainability, and model governance\nWhat We Look For in This Role\nA hands-on AI engineer who enjoys solving real business problems\nA strong data scientist with engineering mindset\nA future technical leader who can grow and guide an AI team\nSomeone who can balance innovation with robustness and maintainability\nA pragmatic decision-maker who chooses the right AI approach for each problem\nWhat This Role Is Not\nA purely research-focused role\nA PoC-only or experimentation-only position\nA narrow specialization without system-level thinking\nIf you enjoy building production-grade AI solutions, working across ML and GenAI, and growing into a technical leadership role, this position offers the opportunity to shape how AI is delivered within AMGS 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