苹果AIML - Software Engineer, Machine Learning Platform & Infrastructure

As a member of the AIML team, you will design, implement and ship scalable, reliable and easy-to-use machine learning platform and tools that will be used by Apple product teams. You will also collaborate with teams across Apple, who are building the new, compelling intelligent applications in the world. You bring a strong hands-on mentality that enables you to own engineering projects from inception to shipping product. You will also be a trusted advisor for best practice machine learning development.

• In this role, you will • - AI Solution Development: Design, develop, and deploy AI-driven applications, across domains, such as machine learning, NLP, and computer vision, addressing both business requirements and end-user needs. • - Agent Design and Development: Design and implement intelligent agents within multi-agent systems, enabling real-time collaboration based on pre-defined goals, strategies, and data exchanges. Develop agent-based models to optimize decision-making and interactions. • - MCP Integration: Extend and integrate Multi-Agent Coordination Platforms(MCP) to optimize resource allocation, communication, and decision-making across multiple agents in shared environments. • - Collaboration with Data Science Teams: Collaborate with data scientists to refine algorithms, optimize models, and enhance AI performance, focusing on model tuning, feature selection, and performance benchmarking • - Testing and Validation: Conduct rigorous testing and validation of AI models, including unit testing, integration testing, and A/B testing, to ensure accuracy, reliability, and scalability before deployment. • - Monitoring and Maintenance: Monitor deployed AI models, track performance metrics, and implement continuous improvement strategies, including model re-training and updates based on real-world data and evolving business needs.

• Lead hands-on design and development efforts primarily using Python, building robust, scalable, and customer-focused AI/ML solutions. • Engage directly with key enterprise customers to strategize, architect and implement AI driven, Agentic AI solutions leveraging Azure AI services including Azure OpenAI, Azure ML. • Translate complex requirements into practical, well-architected technical solutions. • Develop end-to-end, rapid prototypes, involving data ingestion, validation, processing, and model deployment using Azure platform components. • Build, customize, and optimize AI models and related components for customer-specific use cases. • Integrate AI solutions with full-stack architectures, preferably leveraging experience with JavaScript frameworks (e.g., Node.js, React) and/or .NET ecosystems. • Establish and maintain robust CI/CD and ML Ops pipelines, leveraging Azure DevOps, Github for automated deployments. • Proactively explore diverse datasets to engineer novel features and signals that significantly enhance ML performance. • Participate actively in every phase of the model lifecycle from conceptualization, training, fine tuning, validation, and deployment, to continuous monitoring and improvement.

• Design, develop, and deploy robust AI/ML systems with high-quality, scalable, and maintainable code • Translate complex, ambiguous requirements into clear technical plans and lead project execution across engineering efforts • Build scalable infrastructure and platforms to support cutting-edge machine learning workflows, including agentic systems that can plan, reason, and act autonomously • Research and apply state-of-the-art ML techniques—including LLMs, custom model training, and RAG/agent-based architectures—to real-world hardware challenges • Stay current with the fast-evolving AI/ML landscape, continuously improving our tools, systems, and methods to maintain a technical edge • Provide technical mentorship, foster a culture of excellence and inclusion, and help grow team capabilities • Lead design discussions, author technical documentation, and provide thoughtful, actionable feedback to peers • Represent the team in executive reviews, product demos, retrospectives, and cross-functional forums