校招推荐岗位-Pinterest
Masters Machine Learning Internship 2023 (USA)
Remote,United States
Job ID: UO16512831
Summary
KEY RESPONSIBILITIES
Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problemsCollect, analyze, and synthesize findings from data and build intelligent data-driven model.
Write clean, efficient, and sustainable codeUse machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across discovery, ads and search.
Take proactive ownership over the completion and quality of your project and tasks and know when to ask for guidance.
BASIC QUALIFICATIONS
Working towards a Masters in Computer Science, Mathematics, Statistics, or another related field.
Familiarity with Python, Javascript, Java, HIVE, MySQL, Redis, Solr or HadoopInterest in learning new programming languages and technologies.
Strong communicator, team player, and a thoughtful and efficient problem solver.
Previous industry experience is a plus.
Comfortable working in a fast paced environmentPassion for applied ML and the Pinterest productMust be graduating December 2023 or later.
Software Engineering Intern (USA)
Remote,United States
Job ID: UO16512832
Summary
KEY RESPONSIBILITIES
Take ownership over the completion and quality of your tasks and project while incorporating guidance from your mentor, manager, and peers.
Execute scoped technical tasks end-to-end to help build the future of Pinterest Deliver code that is well-docum.
BASIC QUALIFICATIONS
Currently pursuing a degree in Computer Science (CS) or related technical field2+ years of CS classes under your belt (Intro to CS and Algorithms, Advanced Algorithms, Operating Systems and Data Structures are all great!)
Must graduate between December 2023 and July 2024.
Ability to demonstrate an understanding of computer science fundamentals, including data structures and algorithms.
Aptitude for JavaScript, CSS, C++, HTML, Python, Java, Go–we use a variety of programming languages and tools.
Non-academic coding experience (i.e. hack-a-thons, code challenges, personal projects, GitHub, Open Source, volunteer coding experience, conference participation, etc.)A curious nature with a desire to tackle and solve complex problem.
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