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Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Naïve Bayes, Neural Networks, regression, image processing, natural language processing.
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We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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Experience in Artificial Intelligence, Natural Language Processing, Machine Learning, Distributed Computing, Chatbot, and Virtual Assistant. Experience with Big Data or Hadoop tools such as Spark, Hive, Kafka and MapR.
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Experience in Natural language processing (NLP), Prompt engineering, Embedding, Vector DB. Fuse’s innovation culture and modern product development teams power the evolution of our commercial products and spark the creation of new businesses and products.
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Expertise in open source data science technologies such as Python, R, Spark, SQL. Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow.
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Experience in the Design and implementation of AI/ML models and solutions using Google Cloud Platform technologies, including but not limited to Vertex AI , BigQuery, AI Platform, TensorFlow Extended (TFX), Dataflow, and Compute Engine.
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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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Delivery experience in Data Engineering with Google Cloud Platform including Big Query, Dataflow, Cloud Data Fusion, Cloud Composer, Dataproc, Cloud Pubsub, Cloud Function etc. Possess deep functional and technical understanding of the Machine Learning technologies (Google’s Cloud Platform, custom and COTS-embedded) and provide prescriptive guidance on how these are leveraged across the Fuse landscape.
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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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Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy. Encourages informed risk-taking and acts as a catalyst for innovation at Fuse; generates practical, sustainable and creative options to solve problems and create business opportunities, while maximizing existing resources.
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Java, Python, ScalaExperience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence.
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Ensure effective designs and quality deliverables in the ML space by designing and developing machine learning and deep learning systems, running machine learning tests and experiments, implementing appropriate ML algorithms.
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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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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 with natural language processing, text mining, or machine learning techniques. Experience with distributed data and computing tools, including MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL.
$106,200 - $242,000 a yearFull-timeExpandApply NowActive JobUpdated Today
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