Research Intern – Human‑Centered Transparency for GenAI Systems job opportunity at Hitachi.

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Hitachi Research Intern – Human‑Centered Transparency for GenAI Systems
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degreeMBA
loacation Saint-Laurent, Quebec, Canada, Canada
loacation Saint-Laurent,..........Canada

Location: Saint-Laurent, Quebec, Canada Job ID: R0116511 Date Posted: 2026-01-28 Company Name: HITACHI ENERGY CANADA INC. Profession (Job Category): Administration & Facilities Job Schedule:  Full time Remote: No Job Description: French version follows: The Opportunity Hitachi Energy has an opening for the position of Research Intern in the field of AI transparency for Generative AI (GenAI) Systems. The hired intern will work under the supervision of Research Scientist(s) in the Hitachi Energy Research center . This position will be held in a hybrid-format or remotely within Canada. Duration of internship : 4 months (can be extended up to 6 months as per need) Start date : May 6th (flexible) Mode of work : Remote or Hybrid (flexible) Renumerated Internship How you’ll make an impact Conduct an in-depth literature survey on AI interpretability, Explainable AI (XAI), and Human-AI Interaction, focusing on transparency in GenAI systems. Investigate methodologies and frameworks that interpret decisions from AI models applicable across diverse domains such as computing, coding, software engineering, and other technical fields. Implement ML/GenAI methodologies to develop solutions for human-centered transparency. Run experiments and prepare codebase. Prepare a technical report, presentation on work accomplished during internship and/or publication in peer-reviewed conference. Your background PhD students/candidates in Computer Science/Engineering, Machine Learning, Software/Electrical Engineering. Excellent senior master’s (thesis-based) students with relevant experience are also welcome to apply. In-depth understanding of AI/ML methodologies required, including model architectures, training and model evaluation techniques . Experience with Python and ML libraries (e.g., Tensorflow/Pytorch, Scipy, SkLearn) is required. Familiar with GenAI implementation, prompting, evaluation, and agent/tool ‑ use patterns (e.g., retrieval ‑ augmented generation, LangChain, etc). Experience with implementing ML/GenAI solutions and applying quantitative and qualitative evaluation metrics. Research experience involving defining problems, exploring potential solutions, and analyzing results, with the ability to clearly present findings to key stakeholders. Good communication skills (both written and spoken). P referred qualification If you have any of the following qualifications, please ensure to clearly mention them in your resume. Familiarity with XAI/ Interpretability libraries and methods (e.g., SHAP/ LIME, feature attribution, causal or counterfactual reasoning, familiarity with mechanistic interpretability literature). Experience with OpenAI/Azure/Open ‑ Source LLMs. One or more first-authored publications in top AI/ML conference/journals. Ability to do critical and innovative thinking. Ability to take lead in realizing ideas. Experience with multi-agent frameworks, and visualization techniques for interpretability. Experience working with large datasets. Only selected applicants will be contacted.  -------------------------------------------------------------------------------- Poste: Stagiaire en recherche – Transparence axée sur l'humain pour les systèmes GenAI L'offre Hitachi Energy a ouvert un poste de stagiaire en recherche dans le domaine de la transparence de l’IA pour les systèmes d’IA générative (GenAI). Le ou la  stagiaire embauché travaillera sous la supervision d’un ou de plusieurs chercheurs scientifiques au centre de recherche de Hitachi Energy. Ce poste est offert dans un format hybride ou à distance au Canada. Durée du stage : 4 mois (prolongeable jusqu'à 6 mois selon les besoins) Date de début : 6 mai (date flexible) Mode de travail : à distance ou hybride (flexible) Stage rémunéré Votre impact Réaliser une étude documentaire approfondie sur l'interprétabilité de l'IA, l'IA explicable (XAI) et l'interaction homme-IA, en mettant l'accent sur la transparence des systèmes GenAI. Étudier les méthodologies et les cadres qui interprètent les décisions issues des modèles d'IA applicables dans divers domaines tels que l'informatique, le codage, le génie logiciel et d'autres domaines techniques. Mettre en œuvre des méthodologies ML/GenAI pour développer des solutions favorisant une transparence centrée sur l'humain. Mener des expériences et préparer la base de code. Préparer un rapport technique, une présentation sur le travail accompli pendant le stage et/ou une publication dans une conférence évaluée par des pairs. Votre expérience Étudiants/candidats au doctorat en informatique/ingénierie, apprentissage machine, génie logiciel/électrique. D’excellents étudiants de maîtrise (thèse) ayant une expérience pertinente sont également invités à poser leur candidature. Compréhension approfondie des méthodologies d’intelligence artificielle et d’apprentissage machine requises, y compris les architectures de modèles, la formation et les techniques d’évaluation de modèles. Une expérience avec les bibliothèques Python et ML (p. ex., Tensorflow/Pytorch, Scipy, SkLearn) est requise. Connaissance de la mise en œuvre, de l'invite, de l'évaluation et des modèles d'utilisation des agents/outils GenAI (par exemple, génération augmentée par la récupération, LangChain, etc.). Expérience dans la mise en œuvre de solutions ML/GenAI et l'application de mesures d'évaluation quantitatives et qualitatives. Expérience en recherche impliquant la définition de problèmes, l'exploration de solutions potentielles et l'analyse de résultats, avec la capacité de présenter clairement les conclusions aux principales parties prenantes. Bonnes compétences en matière de communication (à l'écrit et à l'oral). Qualifications souhaitées Si vous possédez l'une des qualifications suivantes, veuillez les mentionner clairement dans votre CV. Connaissance des bibliothèques et méthodes XAI/Interpretability (par exemple, SHAP/LIME, attribution de caractéristiques, raisonnement causal ou contrefactuel, connaissance de la littérature sur l'interprétabilité mécanistique). Expérience avec OpenAI/Azure/LLM open source. Une ou plusieurs publications en tant que premier auteur dans des conférences/revues de premier plan sur l'IA/le LM. Capacité à faire preuve d'un esprit critique et innovant. Capacité à prendre l'initiative pour concrétiser des idées. Expérience avec les cadres multi-agents et les techniques de visualisation pour l'interprétabilité. Expérience de travail avec de grands ensembles de données. Seuls les candidats sélectionnés seront contactés. Qualified individuals with a disability may request a reasonable accommodation if you are unable or limited in your ability to use or access the Hitachi Energy career site as a result of your disability. You may request reasonable accommodations by completing a general inquiry form on our website. Please include your contact information and specific details about your required accommodation to support you during the job application process. This is solely for job seekers with disabilities requiring accessibility assistance or an accommodation in the job application process. Messages left for other purposes will not receive a response. 

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