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If you are intrigued by significant challenges in data engineering, distributed systems, and machine learning, and are keen on contributing to a groundbreaking technology platform, this role awaits you.
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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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Experience working with one or more of the following: frontend or backend web development, data engineering, data analysis, data science, data visualization, machine learning, DevOps, site reliability engineering, and cloud architecture.
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Bachelor’s degree with six or more years of relevant work experience as a Data Scientist practicing model development and production for business applications; Or a Master's Degree in Computer Science, Statistics, Math, Economics, Engineering, or Data Science related fields with two or more years of relevant experience as a data scientist or machine learning engineer.
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We're looking for software engineers that have experience in languages like Java, Ruby and Python and are interested in working in domains like big data analytics, search and discovery, and machine learning/NLP. In selecting projects, we look for challenging, mission-focused work where our teams can make a significant difference.
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Fluency in python- Technologies you may use include Azure services such as Azure Machine Learning, Azure AI Search as well as python, micro services, docker, CI/CD, Elastic Search, SQL and NoSQL.- Plus for LLM experience and Open AI API- Plus for search technologies and vector databases.
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The Bioz platform combines the work of scientists with advanced NLP and machine learning, to help life scientists in academia and biopharma make faster and smarter research decisions, ultimately speeding up drug discovery and increasing the rate of success in finding cures for diseases.
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Experience in a wide variety of projects utilizing natural language processing, artificial intelligence, data compression, machine learning and search technologies. Theoretical and practical experience with modern machine learning algorithms and tools, including deep learning and NLP.
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We employ scalable cutting-edge machine learning (ML), deep learning (DL), and Natural Language Processing (NLP) knowledge to better target customers and prospects, understand and personalize the content, and context needed to optimize their book-listening experience.
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Experience in one or more of the following areas: NLP, Ranking, Ads, search engine, recommender system, distributed system, and machine learning. Familiar with NLP, CV-related algorithms, technologies, and familiar with large-scale model training and RL algorithms are preferred.
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Establish scalable, efficient, automated processes for large-scale data mining, machine-learning model development, model validation and serving. Your responsibilities will include everything from developing and prototyping innovative retrieval systems with NLP and Transformer, query planning, deep learning to operating and optimizing a scalable distributed inference solutions in a production environment.
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7+ year Experience in Search, Machine Learning, NLP, Large Language Models and applying these techniques at scale. In-depth knowledge of machine learning algorithms and ability to apply them in data driven natural language processing systems.
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8+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, NLP, data mining or artificial intelligence. Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules-based models.
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Engage with Machine Learning Engineers to determine how data quality variations influence LLM model performance. Strong understanding of machine learning principles, especially in the context of NLP and LLMs.
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In this role, you will leverage our robust data and machine learning infrastructure to implement new ML solutions to make the consumer search experience more relevant, seamless, and delightful across grocery, convenience, and many other retail categories.
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