S'INSCRIRE

Offres d'emploi

Trouvez des postes près de chez vous, sur site, hybrides ou à distance.
  • Emplois similaires à : SoC Machine Learning Design Engineer
XX
SoC Machine Learning Design EngineerApple • United States
Postuler Maintenant
XX

SoC Machine Learning Design Engineer

Apple
  • US
    United States
  • US
    United States
Postuler Maintenant

À propos

Role Number:
200623433-0836
Summary
At Apple we believe our products begin with our people. By hiring a diverse team, we drive creative thought. By giving that team everything they need, we drive innovation. By hiring incredible engineers, we drive precision. And through our collaborative process, we build memorable experiences for our customers! These elements come together to make Apple an amazing environment for motivated people to do the greatest work of their lives. You will become part of a hands-on development team that sets the standard in cultivating excellence, creativity and innovation. Come help us design the next generation of revolutionary Apple products. We are looking for a forward-thinking and unusually talented engineer. As a member of our dynamic group, you will have the rare and rewarding opportunity to craft and implement methodologies and solutions with a high impact on upcoming products that will delight and inspire millions of Apple’s customers every single day. In this role, you will be directly involved in our SoC design machine learning efforts, collaborating right alongside our internal multi-functional teams, and using your expertise in machine learning to improve productivity and optimizations across several SoC design related functions spanning from design to validation.
Description
As a member of the SoC design machine learning team, you will be part of a dynamic team that is building the most efficient application processors on the planet, powering the next generation of Apple products.
Your expertise in machine learning will be instrumental in optimizing for efficiency, quality and speed for our chip-design process.
You’ll play a crucial role in developing generative AI and machine learning solutions for optimizations in RTL Design, Verification, and Power/Performance/Area efforts.
You will collaborate closely with our internal multi-functional teams as well as the AIML organization at Apple to understand domain-specific needs and tailor machine learning solutions to these domains.
As part of this role, you will keep abreast of emerging technologies in machine learning and chip design to ensure our solutions remain state-of-the-art.
Prior leadership experience a plus.
Minimum Qualifications
Minimum of BS + 10 years relevant industry experience.
Preferred Qualifications
Practical experience and knowledge of generative AI and modern machine learning methods.
Experience with any of the following: RAG systems including embedding models, retrieval strategies, and context optimization techniques. Generative AI pipeline development. AI evaluation and testing proficiency including designing test suites and implementing human evaluation frameworks. Experience with AI coding assistants. Experience with AI infrastructure protocols such as MCP.
Experience with Deep neural networks and reinforcement learning is a plus
Solid math background and understanding of algorithms and data structures
Experience with current deep learning frameworks, such as PyTorch, TensorFlow, JAX or MLX
Experience with hardware description languages like Verilog, SystemVerilog or VHDL.
Experience with Chip design and verification front end flows is a plus: Working verification experience with UVM testbenches. Working experience with front-end tools such as Static timing analysis and CDC/RDC.
Strong communication and collaboration skills, with the ability to work efficiently in cross-functional teams
Master's or PhD with relevant publications preferred but not required.
  • United States

Compétences linguistiques

  • English
Avis aux utilisateurs

Cette offre provient d’une plateforme partenaire de TieTalent. Cliquez sur « Postuler maintenant » pour soumettre votre candidature directement sur leur site.