Apple is inviting applications for its Computer Vision and Machine Learning Research Internship focused on Large Language Model (LLM) Efficiency in Zurich, Switzerland. The opportunity is designed for doctoral researchers seeking to advance artificial intelligence research, develop innovative machine learning methods and collaborate with leading research scientists and engineers. The internship focuses on improving the efficiency of frontier machine learning models, including large language models and diffusion models. Successful candidates will contribute to research projects involving model training, inference optimisation, computational efficiency and emerging AI technologies across Apple’s ecosystem. The position is particularly suitable for PhD candidates in computer science, engineering, data science, applied mathematics or related disciplines who have demonstrated research expertise and published work at leading machine learning conferences. Internship Details Organisation: Apple Position: Computer Vision and Machine Learning Research Intern – LLM Efficiency Location: Zurich, Switzerland Research area: Machine Learning and Artificial Intelligence Job reference: 200686571-4170 Date posted: 30 September 2026 Preferred commitment: Six months Preferred start date: As early as possible, subject to the stated eligibility requirements. Application deadline: Not specified in the supplied announcement. About the Internship The research internship offers doctoral candidates an opportunity to participate in advanced machine learning research within Apple’s research and engineering environment. Interns will contribute throughout the research process, from identifying promising research questions and reviewing existing literature to developing new approaches, implementing prototypes and conducting large-scale experiments. The work may involve running experiments across multi-node, multi-GPU systems, analysing results, preparing scientific papers and submitting research findings to leading conferences. The team brings together expertise in computer vision, machine learning, robotics, computer graphics and related fields. Its research contributes to technological developments across Apple’s products and services, with an emphasis on building efficient and effective AI systems. Key Research Areas The internship focuses on improving the performance and efficiency of advanced machine learning models. Areas of interest include: Large language model training and inference efficiency. Frontier machine learning models and diffusion models. On-device machine learning models. Speculative decoding techniques. Contextual sparsity and computational optimisation. Model quantisation and compression. Efficient deep learning architectures and systems. Researchers may explore innovative techniques that reduce computational demands while maintaining model performance, enabling more efficient deployment of AI technologies. Minimum Qualifications Applicants must be working towards a doctoral degree in computer science, engineering, data science, applied mathematics or an equivalent discipline. Candidates should demonstrate proven research expertise in machine learning and have a publication record in relevant conferences, such as NeurIPS, ICLR, ICML or COLM. Strong software engineering skills are required, particularly experience working with complex systems involving multiple programming languages. Fluency in Python is also essential. Apple prefers candidates who can commit to approximately six months. However, the supplied announcement specifies a preferred start no later than March 2026, which predates the posting date of 30 September 2026. Prospective applicants should confirm the current start-date requirements directly with Apple before applying. Preferred Qualifications Additional qualifications that may strengthen an application include: Expertise in machine learning algorithms and established deep learning practices. Experience with machine learning frameworks such as PyTorch or TensorFlow. Strong software development skills and an understanding of reliable engineering practices. Ability to produce clean, maintainable and well-tested code. Experience designing, implementing and evaluating large-scale machine learning experiments. Candidates should be prepared to demonstrate their research contributions, technical capabilities and ability to collaborate on complex scientific projects. Why Consider an Internship at Apple? Apple offers researchers an opportunity to work alongside experienced scientists and engineers on challenging machine learning problems. The position provides exposure to collaborative research, experimental development and the preparation of scientific publications for selective conferences. The company’s stated workplace values include a commitment to its mission, modesty in collaborative problem-solving and focused working practices. Apple also emphasises inclusion, equal opportunity and reasonable accommodations for applicants who require them. The internship may be particularly valuable for doctoral researchers interested in pursuing careers in industrial AI research, machine learning engineering or advanced computational science. How to Apply Interested candidates can review the official vacancy and submit their applications through Apple’s careers website. Search for the position using the title “Internship Computer Vision & Machine Learning Research – LLM Efficiency” or reference number 200686571-4170, and select Zurich, Switzerland, as the location. Applicants should prepare an up-to-date CV highlighting their doctoral research, relevant publications, Python programming experience, machine learning expertise and contributions to projects involving deep learning systems. Candidates should also verify the preferred start date and current application status through the official vacancy before submitting their applications. VISIT OFFICIAL WEBSITE TO APPLY For more opportunities such as these please follow us on Facebook, Instagram, Twitter, LinkedIn and WPChannel Disclaimer: Global South Opportunities (GSO) does not take ownership or credit for the opportunities shared on this platform. All opportunities are sourced from official announcements and external sources for informational purposes only. Applicants are encouraged to verify all details, deadlines, and eligibility requirements from the official source before applying. Opportunities may be updated or changed by the providing organisations.