全球人工智能：专注为AI开发者提供全球最新AI技术动态和社群交流。用户来源包括：北大、清华、中科院、复旦、麻省理工、卡内基梅隆、斯坦福、哈佛、牛津、剑桥等世界名校的AI技术硕士、博士和教授；以及谷歌、腾讯、百度、脸谱、微软、华为、阿里、海康威视、滴滴、英伟达等全球名企的AI开发者和AI科学家。
内容来源：Google 编辑：徐征
1、软件工程师
工作地点：中国 上海市
Responsibilities：
设计、开发、测试、部署、维护和改进软件。
合理安排各个项目的优先顺序，确保每个项目都能按时完成，并交付出色的工作成果。
基本要求：
计算机科学或类似技术领域理学学士学位（或具备同等水平的实践经验）。
具有一种或多种通用编程语言方面的软件开发经验。
在以下至少两个领域具有工作经验：网络应用开发、Unix/Linux 环境、移动应用开发、分布式并行系统、机器学习、信息检索、自然语言处理、网络、大型软件系统开发、安全防护软件开发。
工作能力强，具有良好的英文沟通（书面和口头）能力。
优先条件：
拥有工程、计算机科学或其他相关技术领域的硕士或博士学位，或在这些领域接受过继续教育，或具有相关工作经验。
具有一种或多种通用编程语言方面的经验，包括但不限于：Java、C/C++、C#、Objective C、Python、Java 或 Go。
有兴趣并有能力在需要时学习其他编码语言。
工作地点：Singapore
Responsibilities：
Deliver superb technical training from the GCP Curriculum to diverse audiences (e.g. partners, customers, Googlers etc.) and to individuals from across a wide range of roles such as Solution Architects, Developers, Data Engineers, Sales Engineers etc.
Participate in training planning conversations with strategic customers/partners etc. and work on tailoring content for those audiences as required.
Evaluate, train, audit and coach trainers from our partner training companies.
Provide direct field feedback to the Curriculum Development team and work on updating content as/when required.
Ensure your training schedules are published and any content updates are recorded as required.
Minimum qualifications:
Bachelor’s degree in Computer Science, Maths or related field or equivalent practical experience.
Cloud programming experience. (i.e. Python, Java, .NET, Node.js, Go). Data science/ML experience (i.e. Statistics, ETL, Machine Learning, AI).
Experience with data processing technologies Hadoop, Spark, Kafka, etc. Experience in SQL and NoSQL database technologies for both transaction processing and data analytics.
Ability to travel domestically and internationally.
Preferred Qualifications：
GCP Data Engineer Certification or equivalent.
Experience creating data science models, dashboards, and/or data pipelines.
Experience providing training to a diverse set of customers, from startups to Fortune 100 companies, and to diverse audiences from C-level executives to students in public courses and/or been in client facing technical consulting/educating type role.
Experience creating, maintaining and/or delivering content in a fast-moving technology area, while also being comfortable working in a fast growing, dynamic and sometimes ambiguous environment.
Experience instructing/teaching developers/technical students in adopting new technologies.
3、Software Engineer, Machine Learning
工作地点：Mountain View, CA, US
Responsibilities：
Participate in cutting edge research in artificial intelligence and machine learning applications.
Develop solutions for real world, large scale problems.
Minimum qualifications:
BA/BS degree in Computer Science or related technical field or equivalent practical experience.
2 years of work or educational experience in Machine Learning or Artificial Intelligence.
1 year of professional software development experience.
Experience with one or more general purpose programming languages including but not limited to: Java, C/C++ or Python.
Preferred Qualifications：
MS or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.
Experience with one or more of the following: Natural Language Processing, text understanding, classification, pattern recognition, recommendation systems, targeting systems, ranking systems or similar.
4、Imaging and Vision Architect
工作地点：Mountain View, CA, US
Responsibilities：
Invent imaging pipeline blocks suitable for hardware implementations.
Evaluate the architectural design and algorithms for digital photography, computer vision or machine intelligence scenarios.
Design, define and specify computer vision and image/video processing IP. Author hardware specifications for efficient and practical implementation.
Work with SOC architecture team to understand and improve the architecture and use cases.
Work with the image quality and software teams to understand their requirements and to improve the designs.
Minimum qualifications:
MS degree in EE or CS or equivalent practical experience.
Experience in C or C++.
Experience in digital imaging and computer vision methods and algorithms.
Experience in imaging or vision pipeline.
Preferred Qualifications：
MS or PhD degree in Computer Science, Electrical Engineering or related field or 5 years of industry experience.
Experience developing hardware IP.
Experience in array cameras, computational photography techniques, depth sensing cameras and others.
Deep understanding of machine learning or image/video processing algorithms for consumer photography or mobile applications.
Understanding of image quality metrics.
5、Big Data Deployment Engineer, Cloud Professional Services
工作地点：美国 芝加哥
Responsibilities：
Work with customers to overcome technical obstacles, answering questions and proposing solutions on-the-fly.
Validate partner recommendations/solutions and ensure the right partners are engaged with customers. Understand customer needs and help shape Google’s long-term product strategy.
Package solutions into a published portfolio of best practices for use by our partners and other customers. Be a champion of Google’s “product innovation story”.
Research and test solutions, including authoring sample code, to solve customer technical obstacles.
Travel up to 30%.
Minimum qualifications:
BA/BS degree in Computer Science or related technical field or equivalent practical experience.
Experience architecting, developing, or maintaining production-grade cloud solutions in virtualized environments such as Google Cloud Platform
Experience in writing software in one or more languages such as Python, Go, Java, Java, C++, or similar.
Experience with networking and web standards such as DNS, DHCP, TCP/IP, HTTP, web security mechanisms, proxies, firewalls, load balancers.
Preferred Qualifications：
Hands-on experience in big data, information retrieval, data mining or machine learning.
Experience designing and deploying large-scale distributed data processing systems; experience with MapReduce or Hadoop.
Strong customer-facing communication and careful listening skills. Proven success in and genuine enthusiasm for working directly with customer technical teams.
Strong foundation in computer science, with strong competencies in data structures, algorithms and software design.
Familiarity with open source server software (such as Apache, NGINX, RabbitMQ, Redis, Elasticsearch, Jetty).
6、Software Engineer, Google Hardware Image Processing
工作地点：Mountain View, CA, US
Responsibilities：
Develop state-of-the-art consumer imaging analysis algorithms
Work with the camera hardware team to co-develop data collection systems
Work with the Android Camera team on instrumentation and on-device measurements
Minimum qualifications:
BA/BS degree in computer science, electrical engineering, computer engineering, math or physics or equivalent practical experience.
3 years of experience in image algorithm development or image analysis
Experience with C++, Python, OpenCV
Preferred Qualifications:
Signal processing experience and understanding of color spaces and image quality metrics
Experience with machine learning applied to imaging
Interest in consumer cameras and photography
Ability to navigate through ambiguity, manage and coordinate multiple project assignments simultaneously in a fast-paced, deadline-driven environment, accepting ownership and accountability of the process and deliver on commitments
Leadership skills and excellent communication and interpersonal skills with the ability to work with a wide variety of departments
7、Software Engineer, Research and Machine Intelligence
工作地点：Zürich, CH
Responsibilities:
Participate in cutting edge research in artificial intelligence and machine learning applications.
Develop solutions for real world, large scale problems.
Minimum qualifications:
BS degree in Computer Science, related technical field or equivalent practical experience.
Preferred Qualifications:
MS or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.
Experience coding in C, C++, Java, or Python.
Strong background in Machine Learning or Artificial Intelligence
Extensive knowledge of Android and/or WebKit.
8、Research Scientist, Google Brain (Canada)
工作地点：Montréal, CA
Responsibilities:
Participate in cutting edge research in machine intelligence and machine learning applications.
Develop solutions for real world, large scale problems.
Minimum qualifications:
PhD in Computer Science, related technical field or equivalent practical experience.
Experience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence).
Programming experience in one or more of the following: C, C++, Python.
Contributions to research communities and/or efforts, including publishing papers in machine learning venues (e.g: JMLR, ICLR, NIPS, ICML, ACL and CVPR).
Preferred Qualifications:
Relevant work experience, including full time industry experience or as a researcher in a lab.
Strong publication record.
Ability to design and execute on research agenda.
工作地点：South San Francisco, CA, US
Responsibilities:
Grow and manage teams of analysts including career development, technical leadership, collaboration with engineers and setting team priorities.
Lead cross-functional projects, managing multiple projects with competing priorities simultaneously.
Communicate findings and assessments to senior management and key stakeholders.
Minimum qualifications:
Bachelor's degree in a quantitative discipline (e.g., statistics, operations research, biostatistics, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering) or equivalent practical experience.
Experience in applied statistics in the area of life science and health outcomes research. For example, use of linear models, multivariate analysis, stochastic models, and sampling methods.
Hands on understanding and use of machine learning techniques.
Previous experience in management and career development of analytical teams.
Preferred Qualifications:
Advanced degree in a quantitative discipline (e.g., statistics, operations research, biostatistics, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering)
Previous experience with healthcare/lifescience data analysis and experiment design.
Experience and background in deep learning.
Experience in clinical study design and statistical analysis planning.
Skills for articulating business questions and using mathematical techniques to arrive at an answer using available data. Experience translating analysis results into business recommendations, which includes the ability to communicate complex statistical concepts to non-statisticians.
Collaborative skills to work with teams to understand the possibilities and limitations of statistical techniques in various settings.
10、Bioinformatics Machine Learning Software Engineer, X
工作地点：Mountain View, CA, US
Responsibilities:
Grow and organize a software team in a startup environment inside X.
Work closely with Research, Hardware, and Product teams. Focus on de-risking both the technical and business priorities.
Lead the development of novel Machine Learning techniques as the need arises.
Maintain ongoing partnerships with advisors in teams across Alphabet to apply, modify, and develop new algorithms and software tools as necessary.
Minimum qualifications:
BA/BS degree in Computer Science or related technical field or equivalent practical experience.
5 years of experience programming in C++ and/or TensorFlow.
Experience with deep learning tools and techniques, and/or reinforcement learning.
Applied Machine Learning experience to solve real-world problems such as image classification, anomaly detection, ranking, etc.
Preferred Qualifications:
MA/MS or PhD in Computer Science or related technical field or equivalent work experience.
Experience handling 2D and 3D image data.
Experience solving TB scale data integration challenges.
Experience working in a startup environment. Strong analytical problem solver and self-starter who is comfortable working in ambiguous environments.
Familiarity with computer vision, graphics and/or image processing.
Familiarity with biology or bioinformatics.
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