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Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)Primary Location.
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Lead Data Scientist - Search and Browse (NLP, LLMs, Information Retrieval) page is loaded. Lead Data Scientist - Search and Browse (NLP, LLMs, Information Retrieval) Sr Data Scientist - Search (NLP, Applied ML, Information Retrieval.
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We'll also promote innovative thinking as well as the opportunity to utilize cutting-edge machine learning algorithms and NLP techniques to improve our Mobile and Web Search systems at Target.
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Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization.
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Experience contributing to an open sourced machine learning framework (tensorflow / jax / pytorch / torchscript / mxnet / tensorrt). Currently, we are looking for Engineer Manager - Machine Learning Infrastructure to join our team to support and advance that mission.
$210,000 - $358,000 a yearFull-timeExpandUpdated Yesterday - UpvoteDownvoteShare Job
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Proficiency in data science, machine learning, and analytics, including statistical data analysis and A/B testing. Partner closely with Siri search engineering teams on core machine learning algorithms and systems that are part of Siris ability to understand and respond to requests.
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What You’ll Need: 7+ years of industry experience in one or more of the following: Search, NLP, Ranking, Ads, Recommender systems, and Machine Learning. Using state-of-the-art web-scale machine learning, including cutting-edge NLP, graph-based learning, and multi-modal technology, these teams power a fundamental set of experiences for our over 22 million active customers.
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MLOps - Global SRE team is responsible for the stability of machine learning systems under the Global Monetization Products and Technology organization, to ensure the stable and efficient operations of machine learning models from data preparation, development, training, deployment, serving and so on.
$224,000 - $410,000 a yearFull-timeExpandUpdated Yesterday - UpvoteDownvoteShare Job
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From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
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Java or Golang;•Effective communication skills and a sense of ownership and drive;•Experienced in at least one area of the following areas: personalized recommendations, search engine, machine learning, distributed storage system, big data frameworks is a plus.
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Preferred qualifications include an advanced degree in computer science, machine learning, statistics, or a related field, demonstrating a commitment to continuous learning and expertise in the evolving technological landscape.
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We partner with a large set of cross-functional teams like ML researchers, Product Management, Content Creative teams, Product Design, Data Engineering, and many backend and client engineering teams.
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Build machine learning and statistical models to predict or estimate key signals that are used to optimize marketing campaign performance, such as search engine marketing, customer targeting.
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Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (e.g., AWS, Google Data Analytics, Microsoft Azure) Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark.
$108,000 - $220,000 a yearFull-timeExpandUpdated 2 days ago - UpvoteDownvoteShare Job
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If you have industry experience developing production software for machine learning, especially in areas like recommendation engines, natural language processing, and deep learning for text data, we'd love to talk to you.
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