{"id":2554761,"url":"https://alion.io/job/irth-solutions-data-science-mlgenai-engineer-fre-eng","title":"Data Science ML/GenAI Engineer (FRE/ ENG)","company":{"id":7550,"name":"Irth 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Search","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NER","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Transformers","optional":false},{"name":"CI/CD","optional":true},{"name":"Fine-tuning","optional":true},{"name":"Git","optional":true},{"name":"GitHub Actions","optional":true},{"name":"JavaScript","optional":true},{"name":"MLFlow","optional":true},{"name":"Node JS","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-10-14T18:52:09Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-14T22:34:02Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Data Science ML/GenAI Engineer (Intermédiaire)\nÀ propos d’Irth Solutions\nIrth Solutions est un fournisseur de premier plan de solutions SaaS infonuagiques dédiées à la prévention des dommages, à l’intégrité des actifs, à la mobilisation des parties prenantes et à la gestion foncière.\nNos solutions aident les entreprises des secteurs de l’énergie, des services publics, des télécommunications et des infrastructures à protéger et à gérer leurs réseaux d’infrastructure critiques.\nFort de près de trois décennies d’expérience dans l’industrie, Irth dessert des clients partout en Amérique du Nord et poursuit l’évolution de sa plateforme grâce à de nouvelles capacités axées sur les données, l’intelligence artificielle et l’automatisation.\nÀ propos du poste\nNous sommes à la recherche d’un(e) Data Scientist ML/GenAI pour analyser, structurer et faire évoluer le code existant ainsi que les pipelines de traitement de données afin de les transformer en solutions robustes, évolutives, maintenables et prêtes pour la production.\nDans ce rôle, vous collaborerez étroitement avec les équipes de données et de développement applicatif afin de concevoir et mettre en œuvre des solutions pratiques en intelligence artificielle, apprentissage automatique et GenAI répondant aux besoins d’affaires d’Irth.\nVous travaillerez notamment sur des problématiques liées à la prévention des dommages, l’intégrité des actifs, la gestion foncière et la mobilisation des parties prenantes.\nLa personne idéale est à l’aise dans un environnement couvrant l’exploration et l’analyse de données, l’apprentissage automatique, l’expérimentation avec les technologies NLP/LLM, le développement logiciel et la mise en production de solutions.\nResponsabilités principales\nIA, NLP et GenAI\nConcevoir, prototyper et évaluer des solutions LLM/NLP afin de tester des hypothèses et de répondre à des besoins d’affaires et techniques.\nDévelopper des solutions pour différents cas d’utilisation, notamment :\nClassification de texte\nExtraction d’entités\nRecherche sémantique\nRésumé automatique\nAutres applications de traitement du langage naturel et d’intelligence artificielle\nExpérimenter différentes approches, modèles et techniques afin d’identifier les solutions les plus pertinentes.\nÉvaluer la qualité, la performance et la pertinence des modèles avant leur passage en production.\nData Science et Databricks\nExplorer, préparer, transformer et analyser les données de façon autonome avec Databricks.\nDévelopper et améliorer les pipelines de données nécessaires aux modèles d’apprentissage automatique et aux solutions d’IA.\nPréparer les données pour l’entraînement, l’évaluation et l’utilisation des modèles.\nIdentifier les enjeux liés à la qualité, à la structure et à la disponibilité des données et proposer des améliorations.\nDéveloppement et mise en production\nTransformer les prototypes et preuves de concept concluants en solutions prêtes pour la production.\nDévelopper du code propre, modulaire, maintenable et bien testé.\nAppliquer de bonnes pratiques de génie logiciel et de conception orientée objet.\nAnalyser le code existant, les pipelines de données et les applications afin de déterminer ce qui doit être préservé, amélioré, consolidé ou repensé.\nAméliorer la fiabilité, l’évolutivité, les performances et la maintenabilité des solutions existantes.\nCollaboration et architecture\nCollaborer étroitement avec les équipes de data engineering, développement applicatif et ingénierie afin d’assurer une intégration efficace entre Databricks, les pipelines de données, les modèles et les services applicatifs.\nParticiper aux décisions techniques et architecturales liées aux solutions de data science et d’IA.\nFormuler des recommandations favorisant des solutions efficaces, évolutives et faciles à maintenir.\nContribuer à l’établissement et à l’amélioration des pratiques de développement, de tests et de déploiement.\nCollaborer avec les équipes techniques et les parties prenantes afin de traduire les besoins d’affaires en solutions concrètes.\nÀ quoi ressemble le succès dans ce rôle\nDans ce rôle, vous contribuerez à faire passer les initiatives d’IA et de data science d’Irth de l’expérimentation initiale à des solutions fiables et utilisées en production.\nVotre contribution se traduira notamment par :\nDes prototypes d’IA transformés en solutions de production fiables.\nDes pipelines de données robustes et évolutifs.\nDes capacités d’apprentissage automatique et de GenAI réutilisables.\nDu code propre, testé et maintenable.\nUne meilleure intégration entre les données, les modèles et les applications.\nUne valeur mesurable pour les produits et les secteurs d’activité d’Irth.\nExigences et profil recherché\nExpérience en data science, apprentissage automatique ou domaine connexe.\nExpérience pratique en développement Python et en manipulation de données.\nExpérience avec les concepts et techniques de machine learning.\nIntérêt ou expérience pratique en NLP, LLM et GenAI.\nExpérience avec Databricks et les environnements de traitement de données.\nSolides connaissances en développement logiciel, notamment :\nConception orientée objet\nTests automatisés\nModularité et réutilisabilité du code\nContrôle de version\nBonnes pratiques de développement\nCapacité à comprendre et à améliorer du code et des pipelines existants.\nCapacité à transformer rapidement une idée ou un prototype en solution robuste.\nEsprit analytique, autonomie et capacité à résoudre des problèmes complexes.\nExcellentes aptitudes à la collaboration avec des équipes multidisciplinaires.\nLangues et localisation\nForte préférence pour les candidat(e)s résidant au Québec.\nMaîtrise du français, à l’oral comme à l’écrit, considérée comme un atout important.\nBonne maîtrise de l’anglais, à l’oral comme à l’écrit, afin de collaborer avec les équipes et parties prenantes à travers l’Amérique du Nord.\nPoste entièrement en télétravail au Canada, avec une préférence pour les candidat(e)s basés au Québec.\nAbout Irth Solutions\nIrth Solutions is a leading provider of cloud-based SaaS solutions for damage prevention, asset integrity, stakeholder engagement, and land management. Our technology helps energy, utility, telecommunications, and infrastructure organizations protect and manage critical network infrastructure.\nWith nearly three decades of industry experience, Irth serves customers across North America and continues to expand its platform through data-driven and AI-powered capabilities.\nAbout the Role\nWe are seeking a Data Scientist to help analyze, improve, and evolve existing codebases and data-processing pipelines into robust, scalable, and maintainable solutions.\nIn this role, you will work closely with our data and application development teams to develop practical AI and machine learning solutions that support Irth’s core business areas, including Damage Prevention, Asset Integrity, Land Management, and Stakeholder Engagement.\nThe ideal candidate is comfortable working across data exploration, machine learning, NLP/LLM experimentation, software development, and productionization.\nKey Responsibilities\nDesign, prototype, and evaluate LLM/NLP solutions to test hypotheses and address business and technical needs, including:\nText classification\nEntity extraction\nSemantic search\nSummarization\nOther natural language processing and AI applications\nTranslate successful prototypes into production-ready solutions using clean, modular, maintainable, and well-tested code.\nApply sound object-oriented design and software engineering practices when developing and restructuring solutions.\nAnalyze and understand existing codebases, data pipelines, and applications to determine what should be preserved, improved, consolidated, or redesigned.\nExplore, prepare, transform, and analyze data independently using Databricks to support machine learning models and data-processing pipelines.\nCollaborate closely with the data engineering and application development teams to ensure effective integration between Databricks, data pipelines, models, and application services.\nParticipate in technical discussions and architectural decisions, providing recommendations for effective and maintainable solutions.\nHelp establish development practices that improve the reliability, scalability, testing, and maintainability of data science solutions.\nWork collaboratively with engineering, data, and leadership teams to translate business requirements into practical technical solutions.\nWhat Success Looks Like\nIn this role, you will help Irth move AI and data science initiatives from early-stage experimentation to reliable production solutions. You will contribute to building scalable data pipelines, reusable machine learning capabilities, and maintainable software that delivers measurable value across Irth’s products and industries.\nAI Use in Hiring\nAs part of our hiring process, this role may use artificial intelligence or automated tools to assist in reviewing and screening applications. These tools support, but do not replace, human judgment in hiring decisions.\nRole Type\nThis is a Back fill position.\nCompensation\nThe salary range for this role is CAD $ 80K-120K. This range reflects the base salary only and does not include any other compensation components. Any offers made are dependent on factors including and not limited to experience, skills, and location.\nRequirements\nRequired Qualifications\n3-5 years of experience in data science, machine learning, or ML engineering, with demonstrated experience developing production-quality code beyond notebooks.\nMaster’s degree or equivalent professional experience in data science, machine learning, computer science, statistics, or a related field, with a strong foundation in statistics and modeling methodologies.\nHands-on experience developing NLP and/or LLM-based solutions, including:\nRetrieval-Augmented Generation (RAG)\nEmbeddings and similarity search, including cosine similarity\nHybrid search combining BM25 and semantic search\nText deduplication techniques such as fuzzy matching and MinHash\nText classification and Named Entity Recognition (NER)\nSearch re-ranking\nPrompt engineering\nStrong proficiency in Python, including experience with pandas, scikit-learn, PyTorch, and other relevant machine learning libraries.\nStrong understanding of object-oriented programming, clean code, and software design principles.\nStrong data analysis skills with experience applying statistical methods such as exploratory data analysis, hypothesis testing, and statistical modeling.\nHands-on experience with Databricks or a comparable data/analytics platform, including the ability to independently explore, transform, and prepare data.\nSolid understanding of the machine learning lifecycle, including model training, evaluation, deployment, and production monitoring for issues such as model drift and data quality.\nExperience designing and developing REST APIs to expose data, models, or analytical results to downstream applications.\nStrong written and verbal communication skills, with the ability to collaborate effectively across technical teams with different responsibilities and priorities.\nNice-to-Have Qualifications\nExperience working with news, social media, or other large-scale unstructured text data, including media monitoring, web scraping, or APIs.\nDomain knowledge or professional experience in communications, public relations, media, or related industries.\nFamiliarity with the broader LLM ecosystem, including vector databases/stores, RAG frameworks, and fine-tuning NLP models.\nExperience with MLflow or similar experiment-tracking and model-management tools.\nBasic knowledge of TypeScript and Node.js.\nExperience with CI/CD practices and version control, including Git, GitHub Actions, or equivalent tools.\nAI Use in Hiring\nAs part of our hiring process, this role may use artificial intelligence or automated tools to assist with reviewing and screening applications. 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