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A law firm is seeking a highly qualified and experienced Machine Learning Technology Specialist to join their team in Washington, D.C. The successful candidate will be responsible for drafting patent applications, corresponding with patent offices, advising patent litigation teams, and conducting inventor interviews.
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Transform your career to the next level with GDIT as a Solutions Architect where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.
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Proficiency in data analysis tools (Python, R), machine learning frameworks (TensorFlow, PyTorch), and data visualization tools (Tableau, Power BI). As a Healthcare IT Data Scientist, you will play a vital role in leveraging data analytics and machine learning to drive actionable insights and innovations that enhance patient care, improve healthcare operations, and support strategic decision-making.
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6+ years of professional development experience as Machine Learning Engineer, Data Scientist or related role 6+ years of programming experience with modern languages such as Python, R, C#, Java, or Scala.
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This high performing team works with clients to implement the full spectrum of data analytics and data science, from data querying and wrangling to data engineering, to data visualization, dashboarding, and business intelligence (BI), to predictive analytics, machine learning (ML), and artificial intelligence (AI) as well as robotic process automation (RPA.
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The Machine Learning Engineer will assist with large data pipelines of satellite imagery and help build computer vision models to detect and classify maritime objects in imagery data. Provide technical support to the senior machine learning engineer(s) responsible for developing and advancing other Global Fishing Watch models.
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Expertise in advanced machine learning techniques, including deep learning, data mining, clustering, regression models, predictive modeling, optimization, and ranking. Develop cutting-edge, end-to-end data-driven solutions using a diverse range of machine learning approaches, including supervised, unsupervised, clustering, NLP, computer vision, and ranking.
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The Anti-Money Laundering Modeling and Advanced Data Insights team is on a journey to modernize the way Capital One identifies potential money laundering, terrorist financing, and human trafficking through the use of machine learning, statistics, and other advanced analytic techniques.
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They will also have familiarity with ISR data processing capabilities and maintain a contemporary grasp of Artificial Intelligence and Machine Learning tools that are utilized to support ISR data collection.
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As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. We are looking for a motivated and self organized Machine Learning Engineer who can build and deliver state of the art batch, streaming and real time ML and AI solutions to join the Marketing program to drive powerful experiences for our users.
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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support program evaluations and the development of health policy.
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Conducting cutting-edge research in the fields of artificial intelligence, machine learning, and robotics, specifically as they relate to autonomous vehicle technology. Staying up-to-date with the latest advancements in AI, machine learning, and autonomous vehicle research, and identifying potential areas of improvement for our existing systems.
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Research experience in machine learning, deep learning, and/or natural language processing. Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU.
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Deliver simple solutions to complex problems as a Machine Learning Engineer at GDIT. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
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machine learning jobs Title: learning architect in Washington, DC
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