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Bei uns erleben Sie Lernen und berufliche Weiterentwicklung in einer v\u00f6llig neuen Dimension.</p> <p><strong>Gesund leben, gesund arbeiten<br /></strong>Dar\u00fcber hinaus haben Sie Zugang zu Programmen wie unseren kontinuierlichen Lern- und Weiterentwicklungsprogrammen, der Erstattung von Studiengeb\u00fchren und Mentoring, um Ihr grenzenloses Potenzial auszusch\u00f6pfen \u2013 au\u00dferdem haben Sie die M\u00f6glichkeit, Ihre Lebensqualit\u00e4t durch unsere umfassenden, erstklassigen Leistungsangebote zu verbessern .</p> <p>Die Arbeit, die wir bei Qualcomm leisten, hat Auswirkungen auf das Leben rund um den Globus \u2013 und Sie k\u00f6nnen ein Teil davon sein. Bewerben Sie sich noch heute und entfalten Sie Ihr volles Potenzial..</p>"}}}, "customContent": {"positionSections": [{"title": "Unlock Your Limitless Potential with Qualcomm", "body": "<p>Whether you&rsquo;re launching a new career or ready to explore what&rsquo;s next in the evolution of your talent and expertise, you&rsquo;re about to embark on a career growth journey like no other.</p> <p><strong>Bring out your best, with the best<br /></strong>Our employees make Qualcomm&rsquo;s success possible. We hire the brightest minds and foster a supportive, inclusive culture where your ideas have the power to contribute to world-changing innovations and breakthrough technologies. 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Develops test environments and comprehensive test plans to test code or design for a module; works across teams to collect and manipulate data and evaluate the impact of results, problem solve solutions, and validate software and hardware against specifications; advises less experienced team members and engineers; defines the test plan. Contributes to complex analyses using appropriate tools; reviews analyses completed by others; identifies if an issue has occurred and assists others in addressing issues. Independently identifies issues in code and provides recommendations to improve performance; partners with peers to run algorithms, takes existing algorithms and adds a new feature, and implements new algorithms using software; connecting algorithms as one solution and partition algorithms between software and hardware. Manages project team to complete complex tasks and troubleshoot issues related to the engineering and management of machine learning data. Develops novel machine learning solutions aligned with proposals or roadmaps for complex products; advises team members and less experienced engineers working together on common tasks. Oversees and conducts experiments across several areas to train and evaluate machine learning models and assists other team members to do the same. Evaluates topologies against performance variables and uses the feasibility findings to review the high-level design; provides recommendations for route/topology to maximize performance, quality, and cost within the scheduled design time while reducing risks to the schedule and implementation. Displays deep knowledge in a specific area; acquires advanced knowledge of industry trends, competitors' products, and advances in various engineering fields related to multimedia systems products and technology; reads technical articles and publications; shares knowledge and seeks best practices from open-source community; shares knowledge with others on their team and helps less experienced engineers understand and apply advanced concepts. Stays abreast of current and future trends to make suggestions in strategic discussions within a domain about the product/technology roadmap. Leads technical conversations; identifies technical issues that affect project or other areas of overall system and synthesizes issues into an appropriate document for discussion with the appropriate audience (e.g., project lead, other team leads). Master's degree in Computer Science, Robotics, Electrical Engineering, or related field (PhD preferred). Strong experience in deep learning (transformers, multimodal models) and robotics AI. Proficiency in Python and frameworks like PyTorch or TensorFlow. Familiarity with robotics systems, simulation environments, and ROS 2. Experience with model optimization and deployment on edge or embedded platforms. \u200b Background in vision-language models, policy learning, or robotic foundation models. Experience with dataset curation, teleoperation data, or simulationtoreal transfer. Knowledge of model compression techniques (quantization, distillation) for efficient deployment. 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