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automatique Lieu : Montr\u00e9al, QC -hybride Terme: 4-8 Mois D\u00e9marrage Date : 6 janvier 2025 \u00c0 propos de cette opportunit\u00e9: Le Global AI Accelerator (GAIA) d'Ericsson \u00e0 Montr\u00e9al est une \u00e9quipe de scientifiques des donn\u00e9es et d'ing\u00e9nieurs de donn\u00e9es d\u00e9vou\u00e9s, travaillant sur les d\u00e9fis li\u00e9s \u00e0 la 5G. Il sera pratiquement impossible pour le cerveau humain de comprendre comment ex\u00e9cuter et optimiser un r\u00e9seau 5G, l'apprentissage automatique (ML) et d'autres technologies d'intelligence artificielle (IA) - seront essentiels pour nous de g\u00e9rer cette complexit\u00e9. Machine Intelligence (MI), la combinaison de l'apprentissage automatique et d'autres technologies d'intelligence artificielle est ce qu'Ericsson utilise pour stimuler le leadership \u00e9clair\u00e9 afin d'automatiser et de transformer les offres et les op\u00e9rations d'Ericsson. L'IM est une comp\u00e9tence cl\u00e9 pour permettre les entreprises nouvelles et \u00e9mergentes. Nous nous engageons dans des collaborations universitaires et industrielles pour stimuler la num\u00e9risation d'Ericsson et de nos clients. Dans le cadre de ce stage, vous serez expos\u00e9 et aurez l'occasion d'apprendre et d'explorer dans les domaines techniques suivants: G\u00e9nie logiciel et programmation avec des langages fonctionnels de script tels que Python, Java, Scala, R, etc. Conception, interrogation, administration de bases de donn\u00e9es telles que SQL, NoSQL, GraphDB, etc. Syst\u00e8mes de traitement de donn\u00e9es distribu\u00e9s \u00e0 grande \u00e9chelle tels que Hadoop, Hive, Spark, etc. Pipeline de donn\u00e9es et outils de gestion du flux de travail tels que NiFi, Airflow, etc. Syst\u00e8mes de traitement de flux comme Kafka, Spark Streaming, Akka, etc. M\u00e9thodologie DevOps / MLOps et outils tels que KubeFlow, MLFlow, etc. Tensorflow, SparkML, Scikit-Learn, etc. Infrastructure et outils de cloud priv\u00e9 et public. 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Exp\u00e9rience du d\u00e9veloppement de logiciels et des connaissances en programmation telles que JAVA, Python et les biblioth\u00e8ques d'apprentissage automatique courantes. L'exposition \u00e0 la science des donn\u00e9es, aux concepts d'apprentissage automatique et aux mod\u00e8les de d\u00e9veloppement de logiciels sera une valeur ajout\u00e9e. L'exposition aux technologies de r\u00e9seautage et de t\u00e9l\u00e9communication sans fil sera une valeur ajout\u00e9e pour ce r\u00f4le. Ma\u00eetrise de l'anglais et/ou du fran\u00e7ais. Join our Team Location: Montreal, QC - Hybrid Length: 4-8 Months Start Date: January 6, 2025 About this opportunity: Ericsson's Global AI Accelerator (GAIA) in Montreal is a team of dedicated data scientists and data engineers, working on 5G related challenges. It will be practically impossible for human brains to understand how to run and optimize a 5G network, Machine Learning (ML) and other Artificial Intelligence (AI) technologies- will be vital for us to handle that complexity. Machine Intelligence (MI), the combination of Machine Learning and other Artificial Intelligence technologies is what Ericsson uses to drive thought leadership to automate and transform Ericsson offerings and operations. MI is a key competence to enable new and emerging business. We engage in both academic and industry collaborations to drive the digitalization of Ericsson and our customers. As part of this internship, you will be exposed and given an opportunity to learn and explore in the following technical: Software engineering and programming with scripting functional languages such as Python, Java, Scala, R, etc. Designing, querying, administering databases such as SQL, NoSQL, GraphDB, etc. Large-scale distributed data processing systems such as Hadoop, Hive, Spark, etc. Data pipeline and workflow management tools such as NiFi, Airflow, etc. Stream-processing systems like Kafka, Spark Streaming, Akka, etc. DevOps / MLOps methodology and tools such as KubeFlow, MLFlow, etc. Tensorflow, SparkML, Scikit-Learn, etc. Private & public cloud infrastructure and tools. What you will do Develop data pipelines and machine learning models with help from our data scientists, data engineers, and ML engineers. Researching and implementing ML algorithms and tools. Test and optimize our data & ML pipelines (training or retraining models when needed). Collaborate with our teams to keep our code maintainable, scalable and debug-gable. Ensure high-quality with unit and integration tests. Perform continuous analysis and requirement handling. Develop competence in technical domain. The skills you will bring: Enrolled in an Canadian university in a Bachelor (3rd/4th year), Master or PhD program. Experience with software development and programming knowledge such as JAVA, Python and common machine learning libraries. Exposure to data science, machine learning concepts and software development patterns will be an added value. Exposure to networking and wireless telecommunication technologies will be an added value for this role. English and/or French Proficiency. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. Notice of Job Opportunity - Legal Notices for PERM We encourage you to consider applying to jobs where you might not meet all the criteria. We recognize that we all have transferrable skills, and we can support you with the skills that you need to develop. Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity and Affirmative Action employer, learn more. If you need assistance or to request an accommodation due to a disability, please contact Ericsson at hr.direct.mana@ericsson.com DISCLAIMER: The above statements are intended to describe the general nature and level of work being performed by employees in this position. 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