AI & Data Science Internship - Product Innovation
Philip Morris International
This position is at Philip Morris International
The selection process will be fully managed by Philip Morris International.
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**Be a part of a revolutionary change!** Times are changing at PMI. We’ve chosen to do something big. The world expects us to act responsibly. And we are doing just that by transforming our business and building our future on one clear purpose – to deliver a smoke-free future. This transformation will revolutionize every area of our business. The products we sell. Where we sell them. How they’re manufactured and delivered. The way we talk to our customers and engage with society. It’s the perfect setting place to start your career. As you take your first steps, you’ll have the backing of a multinational business combined with the freedom of a start-up. You’ll bring a positive mindset and fresh perspective to projects that can make a huge difference to so many. About the team The Digital Product Innovation (DPI) team is a specialized group within IT and R&D focused on driving innovation in connected embedded devices. DPI provides digital leadership from ideation to product brief, supporting rapid prototyping, user testing, and early-stage validation. The team leverages advanced technologies—including AI and machine learning—to enhance the entire product lifecycle, from R&D to mass production. Internship Description We are seeking a motivated and curious intern to join our Technology Innovation team for a hands-on project that explores the full spectrum of modern machine learning—from embedded systems to cutting-edge transformer models and large language models (LLMs). **What You’ll Work On:** * Design and implement machine learning algorithms across a range of platforms, from lightweight embedded devices to scalable transformer-based architectures. * Analyze and extract insights from large-scale data lakes, applying statistical and ML techniques to real-world datasets. * Develop and deploy models using Python and standard libraries such as scikit-learn, pandas, NumPy, and PyTorch or TensorFlow. * Leverage cloud technologies for data processing, model training, and deployment pipelines. * Collaborate with cross-functional teams to prototype and validate innovative solutions that support our digital product roadmap. **What We’re Looking For:** * Background in computer science, data science, electrical engineering, or a related field. * Strong programming skills in Python and familiarity with ML libraries. * Interest in both low-level embedded systems and high-level AI models. * Experience or coursework in cloud computing and data engineering is a plus. * A passion for learning, experimenting, and solving complex problems. Roles & Objectives As a Machine Learning Intern, you will play a key role in a forward-looking project that spans the full spectrum of AI—from embedded ML to large-scale transformer models and LLMs. You’ll be part of a dynamic team that values experimentation, rapid iteration, and real-world impact. Key Responsibilities: * Model Development: Design, train, and evaluate machine learning models using Python and libraries such as scikit-learn, pandas, NumPy, PyTorch, or TensorFlow. * Data Engineering: Work with large-scale data lakes to clean, transform, and analyze structured and unstructured data. * Advanced AI: Experiment with transformer architectures and LLMs to solve complex problems and extract insights from large datasets. * Cloud Integration: Use cloud platforms to build scalable pipelines for data processing, model training, and deployment. * Collaboration: Work closely with data scientists, engineers, and innovation leads to align technical solutions with business needs. The intern would be expected to work independently, think critically, and possess strong problem-solving skills. They would also be expected to communicate effectively with team members and stakeholders. **Who we’re looking for:** We seek an enthusiastic intern who embodies curiosity, creativity, and technical prowess. Here’s the ideal candidate: * Enrolled or just finished a degree program in Computer Science, Data Science, or a related field. * Solid Python skills and experience with libraries like scikit-learn, pandas, and NumPy. * Familiarity with deep learning frameworks (e.g., PyTorch or TensorFlow). * Interest in both embedded ML and large-scale models like transformers or LLMs. * Independence and Critical Thinking: You’ll have the autonomy to explore, innovate, and solve complex problems. * Effective Communication: Collaborate seamlessly with team members and stakeholders. **What we offer** Hands-On Experience: The intern will gain practical experience in their field of study, contributing to their professional growth. * Skill Enhancement: Opportunities to learn and apply new skills, including exposure to real-world scenarios. * Networking and Mentorship: Interaction with experienced professionals within the organization. * Flexible Work Environment: A supportive work environment that respects academic commitments. * Project Exposure: Involvement in projects that contribute to the organization’s goals. Our success depends on our talented employees who come to work here every single day with a sense of purpose and an appetite for progress. A condition of commencing the internship with a chosen candidate is that the candidate possesses valid documents authorizing legal residence and work in the territory of the Republic of Poland for the entire duration of the internship. The company reserves the right to verify these documents before signing the contract. Each person who sends the application will receive information about its status. #LI-Hybrid *At PMI we run the business in line with ethical principles and encourage SpeakUp culture. We care for equal chances and fair treatment. If you find anything that violates these principles in this job offer or the recruitment process, you may contact our Ethics and Compliance Team at [E-Mail auf joinrs.com ansehen](mailto:E-Mail auf joinrs.com ansehen). Read more about Ethics&Compliance at PMI – [here](
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