Multi-Modal LLM Research Engineer, Model Optimization and Algorithms Develo at Apple
Sunnyvale, California, USA -
Full Time


Start Date

Immediate

Expiry Date

29 Jun, 25

Salary

143100.0

Posted On

29 Mar, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Learning Techniques, Keras, Network Optimization, Python, Uncertainty, Publications, Machine Learning, Conferences, C++, Computer Science, Research, Computer Engineering

Industry

Information Technology/IT

Description

SUMMARY

Posted: Feb 25, 2025
Weekly Hours: 40
Role Number:200592777
The System Intelligence and Machine Learning (SIML) organization at Apple is looking for a Multi-Modal LLM Research Engineer to help shape the future of on-device Apple Intelligence. In this role, you will work at the intersection of large language models, neural network optimizations, and algorithm development, driving innovations that enhance real-world AI experiences for millions of users.

DESCRIPTION

As part of a collaborative team of deep learning experts and software engineers, you will explore the optimal trade-offs between model quality and efficiency, ensuring that innovative Multi-Modal LLMs can be seamlessly deployed on-device. You will translate the latest research into practical engineering solutions or innovate novel technologies, shaping key decisions on on-device model deployment and real-world performance. Working closely with various teams at Apple, you will help design Multi-Modal LLM architectures, refine training paradigms for real-world applications, and develop software optimized for emerging hardware architectures-potentially even influencing future hardware designs. If you want to be part of a science- and results-driven team and are comfortable embracing new challenges in a fast-paced, iterative environment, we’d love to hear from you. Your research and development will directly shape the next generation of Apple Intelligence experiences!

MINIMUM QUALIFICATIONS

  • Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience.
  • Experience on developing/optimizing/training large language models (LLMs), or large computer vision models, or generative AI models.
  • Proven track record to drive scientific investigations and experiments and overcome obstacles and uncertainty in a research environment.
  • Excellent communication and collaboration skills, and have the ability to work hands-on in multi-functional teams.
  • Solid mathematical foundation of machine learning and deep learning techniques.
  • Strong programming skills in Python, solid understanding of C++.
  • Proficiency in at least one deep learning framework (e.g., PyTorch, Keras, TensorFlow, JAX).

PREFERRED QUALIFICATIONS

  • Strong background in research and innovation, demonstrated through publications in top-tier journals or conferences, patents, or impactful industry experience.
  • Experience with network optimization algorithms, e.g. quantization and compression, sparsification, knowledge distillation, or neural architecture search.
  • Deep understanding of computer systems and the interactions between HW and SW.
Responsibilities

Please refer the Job description for details

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