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Experience with the Big Data technologies (Hadoop, Spark, Presto, Kafka, ClickHouse, Flink. Optimize and enhance open source data frameworks, Spark SQL, Presto, Flink etc. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Mumbai, Singapore, Jakarta, Seoul and Tokyo.
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Learning Systems/Leadership certification such as DDI, Achieve Global, Tom Peters, MBTI, etc. Analyzes data within the Learning Management System, and assures data integrity for learning-related business processes, including managing data to demonstrate contract compliance and regional productivity.
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Good knowledge in Querying and analyzing large amounts of data on Hadoop HDFS using Hive and Spark Streaming and working on systems like HDFS, YARN, Hive, HBase, Spark, Kafka, RabbitMQ, Impala, Kudu, Redis, Hue, Tableau, Grafana, MariaDB, and Prometheus.
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Research and develop hybrid machine learning and physics-based software solutions for semiconductor device and thin film metrology. Experience in Azure DevOps is a plus. Hands-on experience in machine learning and TensorFlow framework.
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Job Description Senior Research Engineer, Machine Learning Privacy San Jose Regular R D Machine learning Job ID: M1758 Responsibilities TikTok is the leading destination for short-form mobile video.
$355,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Develop data and model pipelines with tools like Azure ML SDK, Azure Data Factory, Databricks, Spark, or related technologiesDevelop predictive models using machine learning and similar advanced tools to design, prototype, and build next-generation advanced analytics engines and services, which ultimately optimizes customer experience and increases business outcomes.
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Compensation: $200K - $300K+ Depending on experience plus bonus! Proven experience within the semiconductor or CPU IP industry (RISC-V or similar experience a plus) Experience of CPU architecture (multi-core coherence, FPU, DSP, interrupt, Vector, Security, Reset and CDC, Debug.
$300,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Solid knowledge of at least one machine learning framework (e.g. PyTorch, Tensorflow). The ideal candidate for this role has a combination of strong hands-on engineering skills, extensive industry experience working on machine learning projects, and thrives in a fast-paced, high-ownership environment.
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As a Precision employee, you will be collaborating with experts across a diverse array of fields–including neurosurgery, mechanical engineering, machine learning, and microfabrication–to push the boundaries of what is possible.
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Experience in algorithmic research and development of mainstream risk control strategies and LLM systems development experience is a plus. - Priority will be given to those who master the algorithm principles of LLM (Large Language Models), Fine-tuning, Prompt Engineering, vector databases, and Agent application frameworks such as LangChain/Autogen; familiarity with the latest LLM technologies and experience in training or applying them is a plus.
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As a Senior Data Scientist for our team, you'll leverage your expertise in machine learning, deep learning and reinforcement learning to create large-scale, personalized recommendation models for our omni-channel retail platform, with a focus on exploring and implementing cutting-edge technologies like Large Language Models (LLM's.
$234,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Our team at ByteDance Research has been focusing on developing quantum computational chemistry and machine learning tools to help us better understand some fundamental science problems, such as the mechanism of catalyst.
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The Opportunity Adobe is looking for a Machine Learning Engineer who will participate in various stages of the machine learning pipeline, including data collection, cleaning, preparation, model training and fine-tuning, and evaluation.
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Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Expertise in most of the following areas: supervised & unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, and optimization.
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Strong classroom management skills, including Positive Behavior Intervention and Support (PBIS), Conflict Resolution techniques, and Social-Emotional learning strategies. The Education Coordinator is, or will become, familiar with California Common Core State Standards, including those related to social-emotional learning.
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