Senior Applied Research Engineer - Multimodal LLMs for Human Interaction at Apple

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

28 Apr, 26

Salary

0.0

Posted On

28 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Computer Vision, Artificial Intelligence, Multimodal LLMs, Agentic AI, Natural Language Processing, Generative AI, Self-Supervised Learning, Reinforcement Learning, Algorithm Development, Simulation Frameworks, Technical Leadership, Python, Software Engineering, Mentoring, Research

Industry

Computers and Electronics Manufacturing

Description

Are you excited about the amazing potential of foundation models, LLMs, and multimodal LLMs? We are looking for individuals who thrive on collaboration and have a desire to push the boundaries of what is possible today! The Video Computer Vision org is a centralized applied research and engineering organization responsible for developing real-time on-device Computer Vision and Machine Perception technologies across Apple products. In the Human Intelligence team, we balance research and product to deliver Apple quality, pioneering experiences, innovating through the full stack, and partnering with HW, SW, and ML teams to influence the sensor and silicon roadmap that brings our vision to life. DESCRIPTION We are seeking a highly motivated and skilled Senior Applied Research Engineer to join Human Intelligence team. The ideal candidate will have a strong background in developing and exploring capabilities of foundation models and agentic AI systems that enable natural, proactive and personalized human interactions. In this role, you will work on cutting-edge research and engineering problems, collaborating across teams and help shape the technical direction of multimodal and agentic AI systems from research to production. You will: -Lead the research roadmap for multimodal foundation models, identifying key opportunities for innovation in agentic AI and reasoning capabilities. -Design and oversee the implementation of agentic systems, and large-scale simulation and evaluation frameworks that can transition from research prototypes to production-grade technologies. -Mentor and guide junior researchers and engineers, fostering a culture of technical excellence and innovation within the team. -Develop agentic systems with multimodal large language models, focusing on exploring and utilizing diverse data modalities. -Create novel algorithms and models to enhance the performance, safety, and reasoning capabilities of our AI systems. -Work closely with researchers, data scientists, and software engineers to translate complex research findings into practical, user-facing applications. -Maintain deep knowledge of the latest advancements in AI, machine learning, and multimodal agentic systems, and apply this knowledge to drive innovation within the company. MINIMUM QUALIFICATIONS 10+ years of relevant industry experience in Machine Learning, Computer Vision, or Artificial Intelligence. Demonstrated expertise in developing, training, and fine-tuning multimodal LLMs at scale and developing industry scale agentic products. Proven track record of technical leadership, including architecting complex ML systems and leading projects from conception to product deployment. Expert proficiency in Python and modern software engineering practices. Master of Science in Computer Science, Electrical Engineering, or related field (or equivalent practical experience). PREFERRED QUALIFICATIONS PhD in Computer Science, Electrical Engineering, or a related field with a focus on AI, machine learning, or computer vision. Deep expertise in one or more of the following: computer vision, NLP, multimodal fusion, Generative AI, Self-Supervised Learning, Reinforcement Learning, or Agentic AI. Experience applying foundation models to build autonomous or semi-autonomous agents, including planning, task decomposition, and multi-step reasoning. Strong publication record in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, and ECCV. Experience leading major ML initiatives with a proven record of shipping high-impact products to millions of users. Ability to communicate complex technical concepts to executive leadership and cross-functional partners.

Responsibilities

The Senior Applied Research Engineer will lead the research roadmap for multimodal foundation models and oversee the implementation of agentic systems. They will collaborate across teams to translate research findings into practical applications.