The Applied Researcher role within the Video Computer Vision organization focuses on developing efficient multimodal reasoning systems for Apple products. The team aims to create intelligent systems that can understand and act across various modalities while maintaining strict compute, memory, and latency constraints. This position offers the opportunity to innovate on-device intelligence for millions of users, pushing the boundaries of small model capabilities. The role involves collaboration with hardware and software teams to enhance real-time, privacy-preserving experiences.

• MS in Computer Science, Machine Learning, AI, Computer Vision, or a related field or equivalent practical experience.
• Strong foundation in deep learning, with specific experience in LLM or VLM training, post-training, or inference optimization.
• Demonstrated experience working with multimodal models in resource-constrained environments.
• Proficiency in Python and modern deep learning frameworks, preferably PyTorch.
• PhD with research in efficient multimodal reasoning or lightweight VLM architectures.
• Experience training or post-training vision-language models end-to-end.
• Hands-on experience with reasoning techniques such as chain-of-thought distillation and compression.
• Expertise in decoding and serving optimizations.
• Experience combining LLMs with real-time perception models.
• Experience deploying LLM or multimodal models on mobile or edge hardware.
• Familiarity with efficient vision encoders and self-supervised pretraining.
• Interest in Video-LLMs and long-video reasoning.
• Publication record in top-tier venues is a plus.

• Own the reasoning side of the on-device multimodal stack.
• Design compact vision-language models that reason over various content types.
• Compress and distill the reasoning process for efficiency.
• Engineer the decoding and inference path for multi-step reasoning.
• Collaborate with hardware teams, compiler engineers, and ML researchers.
• Focus on efficient reasoning metrics, including latency and power budgets.
• Develop methods for invoking and reasoning over outputs from specialist vision models.
• Explore research questions related to compact representation and scheduling of expert models.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.