Job Description
Join our multidisciplinary team to build agentic GenAI systems, foundation models, and optimization algorithms that accelerate Apple's chip design. We need an AI/ML Engineer who spans the modern AI stack, from high-level reasoning to low-level compute, to fundamentally shape how our silicon teams operate. This role is ideal for a hands-on technical leader who takes novel research to production deployment and thrives at the intersection of ambiguity, scale, and cutting-edge innovation.
You will join a growing team of ML and software engineers developing state-of-the-art AI systems tailored for physical hardware design domains. In this role, you will have the opportunity to:
● Design and build advanced AI agents featuring multi-agent workflows, search and planning algorithms, self-reflection loops, and tool-calling architectures to automate chip design workflows.
● Train, adapt, and scale modern deep learning and GenAI architectures, including transformers, multimodal models, and hybrid generative backbones to solve complex domain-specific tasks.
● Solve challenging numerical optimization problems by writing high-performance custom primitives(e.g., CUDA, Triton, Metal) to make previously impossible experiments computationally viable.
● Partner with hardware and software teams across Apple, translating theoretical ideas and silicon design requirements into actionable engineering tasks.
Preferred Qualifications
Proficiency in C/C++ and GPU microarchitectures, with hands-on CUDA/Triton development experience.
Experience building stateful, multi-turn agentic frameworks and complex execution flows.
Track record of training large-scale models across distributed clusters (including exploration of non-attention architectures).
Familiarity with Physical Design, EDA, or silicon design environments.
Minimum Qualifications
BSc, MSc, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related fields.
5+ years of applied ML/AI industry experience deploying LLMs, foundation models, or complex ML systems in production.
Strong mathematical foundation in linear algebra, probability and statistics.
Track record as a rapid prototyper who defends hypotheses with empirical data and pivots instantly.
Exceptional programming skills in Python and deep expertise in modern deep learning frameworks (e.g.,PyTorch, JAX).
Excellent communication and collaboration skills to successfully bridge the hardware and software domains.
