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Description
Important attributes expected in the role is fluency in algorithm development (prompt optimization, post training / alignment), and experience with automatic evaluation techniques. The role includes the opportunity to partner with world class system engineers to prototype and incorporate bleeding edge algorithmic innovations in the context of emerging agentic experiences Other responsibilities include testing and upkeep of training infrastructure, whiled partnering with safety/security teams on emerging robustness challenges while aligning models/agents to production needs. Ability to interface with large scale data infrastructure is a huge plus. Apple has a thriving Machine Learning research community. It is expected that role offers the candidate an opportunity to form a strong network of collaborators across the company, while sharing research progress with senior technical leaders at a regular cadence.
Minimum Qualifications
PhD, or MSc in Computer Science/Electrical Engineering, or a related field (mathematics, physics or computer engineering); with a focus on machine learning, or comparable professional experience Strong ML and Generative Modeling fundamentals Proven experience in one of the following: Reinforcement Learning, Multimodal Training, Pre-training / Post-training foundation models Proficiency in using ML toolkits, e.g., PyTorch Track record of research contributions demonstrated through publications in top-tier conferences, or open source contributions to algorithm
Preferred Qualifications
Experience with building & deploying Multimodal-LLMs Familiarity with distributed training and large-scale data infrastructure
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