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Showcase your contemporary expertise in Machine Learning, NLP, Reinforcement Learning, and Deep Learning by applying it to the enhancement of algorithms driving Search, Browse, Autocomplete, and Recommendations experiences on Fanatics.
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Data science, machine learning, optimization models, PhD 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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We're looking for top-notch search engineering talents in the area of information retrieval, search indexing, Elasticsearch, Lucene, algorithms, relevance & ranking, data mining, machine learning, data analysis & metrics, query processing, multi-lingual search and multi-modal search.
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Moloco is seeking a passionate and self-starting Product Manager to lead the state-of-the-art machine learning and performance advertising data products for our MCM (Moloco Commerce Media) product.
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They are in search of a talented Machine Learning Scientist | Data Scientist to join their team. You treat machine learning/data science as a true science, including writing up your conclusions in Jupyter notebooks or the like to discuss your findings with other team members, including benchlab scientists.
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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.
$205,000 - $281,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with SQL and statistical programming languages (e.g., Python, R) to implement statistical analysis and machine learning models. Identify key growth and performance opportunities for main Google Ads products across various points of the customer lifecycle (Search, pMAX, Measurement.
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Experience working on search and/or discovery products, including products involving machine learning, recommendation models, ranking, and signal building. Experience leading cross-functional execution with various teams including engineering, data science, design, marketing, partnerships, legal, and policy, to conceptualize, develop, test, and launch impactful features.
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Utilize data-driven approaches and machine learning techniques to optimize product rankings based on user preferences, behavior, and historical data. Collaborate with cross-functional teams including UX/UI designers, engineers, and data scientists to continuously improve the search experience.
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Analyze user behavior, feedback, and market trends to identify areas for improvement in search UX. Evaluate and optimize facets returned in search to ensure they align with user expectations and preferences.
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Create highly scalable classifiers and tools utilizing machine learning, data regression, and rule-based models. At this time, they are seeking Machine Learning Engineering Manager where you will own the product road map and scale their AI products and platform.
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Software Engineers, Machine Learning : Research, design, develop, and test operating systems-level software, compilers, and network distribution software for massive social data and prediction problems.
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Experience with Machine Learning tools (Scikit-learn, TensorFlow, PyTorch, NGS (next generation sequencing ) data formats (e.g. Bam, Fastq,) and Data pipelines (WGS, Broad GATF, nf-core.
ExpandApply NowActive JobUpdated 15 days ago - UpvoteDownvoteShare Job
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The team leverages sophisticated machine learning, data science and big data technologies to understand customers' intent and provide relevant product and services through the best possible experience.
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Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU) Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
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