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Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Nave Bayes, Neural Networks, regression, image processing, natural language processing.
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3+ years of research experience in natural language processing, machine learning, and related fields. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence (for example, human-assisted AI, natural language processing, robotics, 3D perception, and AI platform), energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design.
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Experience and training in cutting-edge research in machine learning, natural language processing (NLP), text mining and computational linguistics. Degree in a quantitative discipline such as Predictive Analytics, Statistics, Mathematics, or Computer Science with coursework in Machine Learning, Deep Learning, and Natural Language Processing; Masters/PhD preferred.
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Design, develop and implement various process improvement tools and techniques including Workflow, Robotic Process Automation (RPA), Optical Character Recognition (OCR), Natural Language Processing and (NLP), Machine Learning (ML) to meet end-to-end business requirements.
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About the RoleAs a Machine Learning Engineer - Technical Lead II for Crowe Intelligent Document Analyzer (CIDA), you will design the future of this document extraction product as it transitions from a combination of Natural Language Processing and embeddings models to fully integrate with Crowe’s in-house Generative AI platform and to leverage Large Language Models (LLMs.
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Strong understanding of conversational AI, natural language processing (NLP), and the principles of Generative AI (GenAI) is highly desirable. As a key member of our interdisciplinary team, which includes Product Managers, UX Designers, Data Scientists, and Machine Learning Engineers, you will play a crucial role in bringing our GenAI projects from concept to reality, ensuring they are not only technologically advanced but also user-friendly and impactful.
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Architect, design and develop advanced AI models forLLM application, focusing on natural language understanding (NLU), natural language processing (NLP), and machine learning.
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As a Machine Learning Engineer - Technical Lead II for Crowe Intelligent Document Analyzer (CIDA), you will design the future of this document extraction product as it transitions from a combination of Natural Language Processing and embeddings models to fully integrate with Crowe's in-house Generative AI platform and to leverage Large Language Models (LLMs.
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Natural Language Processing (NLP). You enjoy machine learning and understand supporting these solutions in a production environment using tools like Docker and Git; you're familiar with Kubernetes.
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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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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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Design, develop, and implement machine learning models and algorithms to solve complex problems across various domains, including but not limited to recommendation systems, natural language processing, and predictive analytics.
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Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment. 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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We are looking for 3 to 5 years of experienced Machine Learning Engineer with a strong background in data science, machine learning (ML), Natural Language Processing (NLP), and Large Language Models (LLM) technology.
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Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and experience deploying machine learning models using containerization technologies (e.g., Docker, Kubernetes). Join our team as a Machine Learning Engineer, where you will play a pivotal role in leveraging data-driven solutions to drive innovation and business impact.
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