About the role
Company description: Ericsson AB Job description: Join our Team About the opportunity Join Ericsson Research and help shape the future of connectivity. AI is central to Ericsson’s 6G vision, enabling intelligent, sustainable, and secure networks for people and industries in the 2030s and beyond. Our work combines machine learning, advanced reasoning, and real network systems, with access to live network data and opportunities to influence global standards and technologies used worldwide. This early-career role suits a recent master’s graduate or someone with a few years of experience in AI/ML. You’ll take on meaningful research from day one, collaborate with global, cross-disciplinary teams, and learn from experienced mentors. A telecom degree or prior radio expertise isn’t required: you can build domain knowledge through hands-on work with radio specialists. We value diverse perspectives and offer an inclusive environment, flexible ways of working, wellbeing support, benefits, and growth opportunities. You don’t need to meet every preferred qualification; curiosity and motivation matter. What you will do • Research, design, and evaluate AI/ML concepts for future radio access networks and AI-native systems, including autonomous, large-scale telecom networks. • Develop algorithms, models, and simulation frameworks. Explore AI applications in radio access networks. • Use modern AI-assisted development tools to prototype and iterate quickly. • Collaborate with experts in radio systems, networking, and hardware, connecting research ideas with practical needs such as performance, scalability, robustness, automation and energy efficiency. • Turn research into prototypes, publications, patents, and contributions to future standards. Share findings, build your research profile, and keep learning with support from senior researchers. Skills you bring • An MSc in AI, data science, computer science, engineering physics, robotics, or a closely related field is preferred. Candidates with an MSc and strong AI research experience are also encouraged to apply. • A strong foundation in modern AI, such as deep, reinforcement, or distributed learning; generative AI; probabilistic modelling; stochastic optimization; or graph-based methods. • Python programming skills and familiarity with ML frameworks such as PyTorch, JAX, or TensorFlow. • Some experience designing, training, or validating ML-driven systems through studies, internships, or personal projects. Familiarity with simulation-based evaluation is valuable. • Interest in AI coding assistants and openness to new tools. Experience with Docker or Kubernetes is a plus. • Interest in telecommunications, networking, or signal processing. Telecom expertise can be learned on the job. • A curious, self-directed approach: you generate and test ideas, learn independently, ask questions, seek expert input, and work through uncertainty. You bring analytical problem-solving, ownership, and collaborative skills, and can communicate clearly, including explaining AI concepts to non-specialists.