Machine Learning Engineer • Mid-Level

Who you are

You have a Master's or PhD in Computer Science, Machine Learning, Electrical Engineering, or a related field, along with equivalent research or industry experience. Your strong background in reinforcement learning and machine learning allows you to tackle complex problems effectively. You are eager to explore the intersection of fundamental research and applied work, contributing to both scientific progress and real-world applications.

You possess a deep understanding of large language models and their intricacies, including instruction following, multi-turn dialogue, and reducing hallucinations. Your experience in developing and scaling reinforcement learning methods equips you to improve reasoning and planning in AI systems. You thrive in collaborative environments, working closely with researchers and engineers to achieve common goals.

What you'll do

As a Machine Learning Engineer at Apple, you will join a dedicated team focused on advancing reinforcement learning for generative AI applications. You will develop and scale methods to enhance reasoning and instruction following in large language models, directly impacting features like Siri. Your responsibilities will include designing and training agents with tool use and planning capabilities, as well as building and refining reward models and datasets.

You will run large-scale experiments, analyze results, and translate your findings into both research contributions and practical improvements for Apple Intelligence. Collaborating with a Europe-based team of approximately 35 RL/ML experts, you will coordinate closely with Apple's foundation model groups in the U.S., ensuring that your work aligns with broader company objectives.

What we offer

At Apple, you will be part of a culture that values diversity and inclusion, where your unique experiences and perspectives are celebrated. You will have the opportunity to work on cutting-edge technology that shapes the future of AI and impacts billions of users worldwide. We encourage you to apply even if your experience doesn't match every requirement, as we believe in fostering a supportive environment for growth and development.