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We are seeking a highly motivated Machine Learning Engineer Co-Op from July 2024 to December 2024, focusing on Natural Language Processing (NLP) and Computer Vision applications. Familiarity with data processing tools, such as Pandas and NumPy. Strong problem-solving and analytical skills, with the ability to think creatively and adapt to new challenges.
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Knowledge of natural language processing (NLP) techniques and libraries. Founded in 2021 by Jonathan Bush, co-founder and former CEO of athenahealth, Zus partners with HIEs and other data networks to aggregate patient clinical history and then translates that history into user-friendly information at the point of care.
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Analyze and gather input in areas including information retrieval, distributed computing, large-scale system design, networking, and data storage, security, artificial intelligence, natural language processing, UI design, and mobile.
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We have a strong preference for building our own backend technology, so you’ll be implementing and working with the latest natural language processing (NLP) techniques and ideas. The Staff Data Engineer will also be charged with team lead responsibilities and will play a big part in roadmap definition and execution.
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Distinct experience in big data processing, analytics, and pipelining using Spark is essential, as well as experience in deep learning, generative AI, LLMs, and NLP.This is a hands-on leadership role which involves leading machine learning teams, building best architectural solutions, mentoring and imparting knowledge about machine learning and data concepts and techniques, as well as driving adoption of standards, processes, and tools to achieve high operational efficiency.
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Strong signal and information processing expertise (statistical signal processing, array processing, signal modeling, linear algebra, probability and random processes, optimization, tracking/data fusion, adaptive signal processing, digital signal processing, information theory.
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Full Time] Senior Analytical Chemist I, Metabolomics at Ginkgo Bioworks (United States) | BEAMSTART Jobs. Support the implementation of software to streamline data processing, data mining, biomarker identification and development of prediction models.
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Proficient in emerging technologies such as deep reinforcement learning, imitation learning, computer vision, and natural language processing, with a focus on their application in robotics.
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Proficiency in complex data extraction or processing using Python, SQL, Snowflake. We are seeking a Data Science Associate to join the Digital Asset Management business and report directly to the VP, Data Science.
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Quantifind's Graphyte platform uncovers signals of risk across disparate and unstructured text sources using artificial intelligence and natural language processing techniques. The base salary range for this full-time position is $110,000 to $140,000.
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Utilize GCP services such as BigQuery, Google Cloud Storage, Dataflow, and data processing and storage. With Confluent, organizations can harness the full power of continuously flowing data to innovate and win in the modern digital world.
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Department Customer Success & Project Management Locations Boston Remote status Fully Remote Employment type Full-time. We are seeking a full-time employee for a fully remote position, ideally based in the Eastern Time Zone (EST) to effectively support clients across different time zones.
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The Bioinformatics Scientist is responsible for analyzing antibody selection data from yeast display, implementing machine learning algorithms to enhance data analysis and lead selection, and managing the data pipeline from raw file processing to database storage.
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Relevant certifications such as CISSP, CCNP, AWS Certified Solutions Architect, or ITIL are a big plus. Leverage In-depth knowledge of Data Recovery, Business Continuity Plans, critical infrastructure management, incident response, vulnerability management, and data protection to ensure Voyager's security.
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As researchers at Stanford and Berkeley, they both worked on language technology to make information accessible to everyone. At the time, machine translation didn’t meet the quality standard for enterprise translations, so Lilt assembled a cutting-edge research team tasked with closing that gap.
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