苹果AIML - Applied Machine Learning Engineer, Answers, Knowledge & Information
任职要求
Minimum Qualifications • BS/MS in Computer Science or equivalent, with 3+ years of industry experience. • Solid experience in data mining, machine learning, natural language processing, and large language models. • Strong programming experience in one or more of the following: Java, C++, Golang. • Hands-on experience working in large engineering teams and large-scale codebases, including code submission/review, CI/CD, testing, and release processes. • Ability to translate abstract goals into actionable, executable plans. • Strong aptitude for rapidly learning new domains, quickly organizing complex project details, summarizing status, and proposing practical solutions. Preferred Qualifications • Proven ability to work under pressure and manage multiple projects with tight deadlines. • Self-starter w…
工作职责
The objective of this role is to elevate Apple’s voice assistant and search to a new level of intelligence and accuracy through advanced machine learning techniques. We are looking for someone with a strong passion for AI-driven applications. In this role, you will develop a deep understanding of user use cases and create high-quality evaluation datasets. You will leverage large language models and search tool integrations to answer user questions across diverse everyday scenarios. A core responsibility will be conducting systematic failure analysis to continuously improve accuracy and user experience. On a day-to-day basis, your work will span model training, tool development, system integration, performance testing, and functional test design.
In this role, you will: - Design and develop advanced optical sensor test stations and integrate sophisticated instrumentation - Build algorithms for calibration, validation, and optimization in high-volume manufacturing environments - Apply advanced data processing or AI/ML techniques to improve test coverage, accuracy, and yield - Collaborate with cross-functional teams to deliver integrated mechanical, electrical, and software test solutions - Debug complex optical-electrical-software issues and lead system commissioning at global manufacturing sites
LLM Application in Customer Service: Design, develop, and iterate on prompts for various LLM applications within the customer service center, including conversational AI, content generation, and summarization. Experiment with prompt formats, styles, and techniques to optimize LLM performance and output quality. Analyze LLM-generated responses, identify biases or limitations, and implement mitigation strategies to enhance customer satisfaction and service performance. Operational Excellence: Identify and propose innovative projects that leverage LLMs to solve complex problems or explore new capabilities in customer service. Conduct research, experiment with cutting-edge techniques, and develop prototypes for potential products or services. Collaborate with data scientists, machine learning engineers, and other stakeholders to integrate prompts and research findings into the broader AI/ML pipeline. Performance Analysis: Analyze the content of customer interactions to generate self-service rate analysis reports, explaining why customers transfer to agents and what can be done to improve these indicators. Generate regular chat-bot performance reports and continuously improve the algorithm model accuracy, customer satisfaction, and service performance of the chat-bot. Team Collaboration: Work closely with relevant function teams to deliver an integrated workflow of demand negotiations, standard creations, and project implementations. Share knowledge and best practices with the team, mentor junior AI operation peer, and contribute to a collaborative learning environment.
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. Starting in 2024, the Innovation Center launched a new Custom Model and Optimization program to help customers develop and scale highly customized generative AI solutions. The team helps customers imagine and scope bespoke use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop and optimize models to power their solutions, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Applied Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. As an Applied Scientist, you will - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges - Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production - Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization - Provide customer and market feedback to product and engineering teams to help define product direction