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Good foundation in Machine Learning (ML), Deep Learning, Large Language Models (LLM) and Natural Language Processing (NLP). Tagged as: Industry , Language Modeling , Machine Learning , Natural Language Processing , NLP , Unspecified.
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As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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Hands-on experience in applying Natural Language Processing (NLP) solutions is a plus. Develop AI-based systems for Natural Language Processing (NLP) Familiar with Spark, MLLib, Databricks MLFlow, Apache Airflow and similar related technologies.
$144,000 - $169,000 a yearFull-timeExpandApply NowActive JobUpdated 21 days ago - UpvoteDownvoteShare Job
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Experienced with traditional as well as modern machine learning/statistical techniques, including A/B testing, Causal Inference, Regression, Classification, Ensemble Methods, Deep Learning, Natural Language Processing, and Reinforcement Learning.
$160,000 - $230,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience in one or more of the following areas: Recommendation Systems, Bayesian inference and Gaussian processes, Time series, GNNs, Information retrieval and Data mining, Natural Language ProcessingDistributed data processing in Hadoop, Spark, BigQuery, or Apache BeamDistributed training.
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Advanced degree in Computational Linguistics, or Computer Science with a focus on Natural Language Processing. 6+ of software industry experience in Data Science or Natural Language Processing.
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Managing distributed teams is a plusProven track record of building products/features using Natural Language Processing, Query Understanding and Semantic Search techniquesExperience with Big Data and search technologies Spark/Hadoop/Kafka and SOLR.
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Hands-on experience in applying Natural Language Processing solutions to challenging real-world problems. Build on top of Open Source LLM (Large Language Models) to leverage a diverse dataset.
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At least one year of experience in the Machine Learning or AI domain, working with technology infrastructure related to Deep Learning, Large Language Models (LLM), Generative AI (GAI), Natural Language Processing (NLP), or other areas.
ExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Natural language processing (NLP) and text mining skills a plus. Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) We solve complex challenges alongside the most influential companies in the industry, using the most advanced algorithms in areas such as machine learning, biometrics, and video processing, combined with world class software and silicon development.
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A deep understanding of modern machine learning techniques and their mathematical underpinning, such as classification, clustering, optimization, deep neural network and natural language processing.
ExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Passion or exposure to areas like machine learning, NLP (Natural Language Processing), multimodal systems, and computer vision. - Exposure to large-scale text data processing or tools like Hadoop/Spark/Hive/Flink.
$112,200 - $205,000 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Strong understanding of machine learning concepts and techniques, including deep learning, reinforcement learning, natural language processing, and computer vision. Experience with cloud platforms such as AWS, Azure, or Google Cloud, and familiarity with distributed computing frameworks (e.g., Spark, Hadoop.
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Experience with computer vision or natural language processing aplus. Extract Transform Load (ETL) experience using Spark, Kafka,Hadoop, or similar technologies. SummaryWe are looking for a Machine Learning Engineer, who has hands-onexperience in machine learning system development, Cloud computing, backenddevelopment and AI/ML. Candidate must have strong NLP exp.
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We are looking for a Machine Learning Engineer, who has hands-on experience in machine learning system development, Cloud computing, backend development and AI/Client. Experience with workflow scheduling / orchestration such as Kubernetes, Airflow or Oozie.
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