Job description

This role is dedicated to transforming engineering productivity and enabling cutting-edge hardware design through the strategic application of machine learning and generative AI. As a Senior AI Engineer, you will bridge the gap between complex hardware engineering workflows and state-of-the-art artificial intelligence. You will architect intelligent agents capable of automating repetitive engineering tasks, analyzing high-dimensional data to surface hidden trends, and tapping into decades of historical design intelligence. By building these systems, you will empower engineers to arrive at critical decisions with unprecedented speed and accuracy, directly influencing the next generation of Apple innovation. 7+ years of experience in AI/ML-related projects, with a proven track record of architecting and deploying production-scale Generative AI solutions. Masters or PHD in Artificial Intelligence, Machine Learning, Computer Science or a related field. Expert-level knowledge of multi-agent system design, including sophisticated orchestration, coordination, and persistent state management. Strong command of Agent Communication Protocols (e.g., MCP, A2A) and frameworks for designing distributed agentic workflows. Expert-level software development skills with a solid foundation in architectural design principles and the creation of scalable, modular systems. Proven ability to lead cross-functional architecture discussions and translate ambitious product goals into robust technical system designs. 10+ years of professional experience in AI/ML-related projects, demonstrating a long-term track record of innovation and technical leadership. Proven ability to build efficient interfaces for agents to invoke APIs, query high-dimensional databases, and interact with custom toolsets. Proficiency in Python (Core and Async) and a strong command of FastAPI or Flask for serving high-performance AI endpoints. Proven success in deploying Generative AI solutions tailored to complex, high-dimensional, and domain-specific engineering data. Prior experience overseeing the full lifecycle of large-scale software applications deployed within an enterprise-grade production environment. Deep understanding of model selection, intelligent routing, and fallback strategies to ensure reliability across multiple LLM providers. Experience developing and implementing rigorous Gen AI evaluation systems to measure the performance, safety, and accuracy of deployed agents

Requirements

Must-haves

7+ years of experience in AI/ML-related projects, with a proven track record of architecting and deploying production-scale Generative AI solutions.
Masters or PHD in Artificial Intelligence, Machine Learning, Computer Science or a related field.
Expert-level knowledge of multi-agent system design, including sophisticated orchestration, coordination, and persistent state management.
Strong command of Agent Communication Protocols (e.g., MCP, A2A) and frameworks for designing distributed agentic workflows.
Expert-level software development skills with a solid foundation in architectural design principles and the creation of scalable, modular systems.
Proven ability to lead cross-functional architecture discussions and translate ambitious product goals into robust technical system designs.
10+ years of professional experience in AI/ML-related projects, demonstrating a long-term track record of innovation and technical leadership.
Proven ability to build efficient interfaces for agents to invoke APIs, query high-dimensional databases, and interact with custom toolsets.
Proficiency in Python (Core and Async) and a strong command of FastAPI or Flask for serving high-performance AI endpoints.
Proven success in deploying Generative AI solutions tailored to complex, high-dimensional, and domain-specific engineering data.
Prior experience overseeing the full lifecycle of large-scale software applications deployed within an enterprise-grade production environment.
Deep understanding of model selection, intelligent routing, and fallback strategies to ensure reliability across multiple LLM providers.
Experience developing and implementing rigorous Gen AI evaluation systems to measure the performance, safety, and accuracy of deployed agents

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaimlpythonllm

Platform: apple
Effort: medium