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As a Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals. Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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KEYWORDS Machine Learning | Physics | Embedded Systems | Signal Processing | Data Analysis | Nvidia | Electrical Engineering | Cloud Computing | Cuda | TensorRT | Radio Frequency | Transmission Processing | Linux OS | Pytorch | Python | Edge Computing.
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AI and Machine Learning: Utilize state-of-the-art AI and machine learning techniques, including natural language processing (NLP), to train the chatbot for accurate and effective communication.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Job title: Machine Learning Engineer. #Machine #Learning #Engineer. You will implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
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4- 8 years of experience as machine learning engineer/data scientist. Aggregate huge amounts of data and information from large numbers of sources to discover patterns and features necessary to build machine learning models for prediction and forecasting.
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To build a world-class research program for AI- and data-driven innovation in human health, the AI Department is seeking five (5) outstanding candidates for early-career faculty positions at Instructor level with an excellent track record in artificial intelligence, and machine learning to join its faculty as a Eric and Wendy Schmidt AI in Human Health Fellow in 2024.
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Strong understanding of Computer Science fundamentals (algorithms and data structures) as well as modern techniques in machine learning and deep learning, deep learning model architectures (C/RNN, attention/memory, autoregressive, etc.
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Work collaboratively with experts from other fields ( e.g. , computational biology, molecular biology, medicinal chemistry, machine learning) to drive harmonized models with innovative features.
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Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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Develop strategies to utilize machine learning to enhance the work of OIG-NYPD. DOI's OIG-NYPD is seeking an Associate Data Analyst who will supervise at least one data analyst while supporting active investigations into the operations, policies, practices and programs of the NYPD.
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Experience with parallel programming, machine learning, bioinformatics, cybersecurity, sparse linear algebra or graph databases is preferred. Experience with machine learning, bioinformatics, cybersecurity, sparse linear algebra, and/or graph databases are highly preferred.
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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. New York City (Hybrid On-Site): $201,400 - $229,900 for Lead Machine Learning Engineer.
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Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions. This role is a unique opportunity for an experienced ML scientist and hands-on NLP/Gen AI/ LLM senior scientist to grow into the next step in their career journey and apply her or his domain expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while mentoring and growing a ML Data Science team.
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Advanced knowledge of Excel and extensive experience with and proficiency in statistical computing software or data analytic environments (e.g., SAS, SPSS, Stata, SQL/NoSQL databases including ETL, Python, R, Tableau), including the ability to analyze large and complex datasets for patterns and trends, and build statistical models.
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machine learning jobs Title: sr data scientist Company: Humana in New York, NY
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