Formal Verification AIML Engineer

Apples Hardware Technologies Formal Verification team is seeking an AI/ML Engineer to work at the intersection of Artificial Intelligence and Formal this role you will explore prototype and build AI-powered systems with a focus on Large Language Models to augment and transform how formal verification is performed on Apple will work closely with formal verification engineers design engineers and EDA tool developers to identify high-impact opportunities and deliver practical domain-specific AI applications.

You will be responsible for:nBuilding domain-specific AI applications that leverage LLMs and other ML techniques to accelerate formal verification workflows from specification interpretation to property generation proof debugging and and fine-tuning LLM-based systems tailored to hardware verification tasks including retrieval-augmented generation (RAG) pipelines agentic tool-use frameworks and domain-adapted with formal verification engineers to deeply understand FV methodologies pain points and opportunities where AI can meaningfully improve productivity quality and novel AI-driven approaches for tasks such as automatic SVA property synthesis natural-language-to-formal-specification translation proof strategy recommendation and intelligent counterexample and integrating emerging AI/ML research into practical production-quality tools and workflows used by the FV best practices and infrastructure for AI application development within the FV organization.

A minimum of a bachelors degree in relevant field and a minimum of 10 years of relevant industry experience.

Strong hands-on experience building AI/ML applications particularly those leveraging Large Language Models (LLMs) including prompt engineering fine-tuning RAG architectures agentic systems or LLM-based tool ability to take AI capabilities from prototype to production you have shipped or deployed AI-powered tools or applications not just trained in Python and modern ML/AI frameworks and tooling (e.g. PyTorch LangChain LlamaIndex Hugging Face or similar).nBackground in formal methods mathematical logic or a strong mathematical foundation whether through academic training (e.g. formal methods type theory automated reasoning mathematical logic) or applied experience. You dont need to be an FV expert but a quantitative and rigorous mindset is interest in domain-specific AI applications you are excited about going deep into a specialized engineering domain rather than building general-purpose AI engineering best practices version control testing API design and building maintainable collaborative communication and interpersonal skills you will work across disciplines with FV engineers design engineers and tooling -directed and comfortable with ambiguity you will need to identify opportunities propose solutions and drive them working on or contributing to LLM tooling frameworks or infrastructure (e.g. inference engines model serving evaluation harnesses).nPrior exposure to hardware design or verification concepts (RTL SystemVerilog assertions EDA tools).nFamiliarity with formal methods SAT/SMT solvers model checking or theorem with code generation or analysis tasks using or PhD in Computer Science Electrical Engineering Mathematics or a related field though exceptional industry experience is equally valued.