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A Glimpse into the Daily Routine of a Machine Learning Engineer. Self-motivated and proactive, with a passion for learning and staying updated with the latest trends and advancements in the field of data engineering.
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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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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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As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
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Demonstrated track record of developing and implementing machine learning models in real-world applications, preferably in the context of quantitative trading or algorithmic trading. We are a leading multi-strategy hedge fund at the forefront of applying cutting-edge machine learning techniques to quantitative trading strategies.
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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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Develop and publish relevant bioinformatics methodologies, pipelines, and algorithms, and stay abreast of the latest advancements in bioinformatics, machine learning, and oncology research.
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Data science, machine learning, optimization models, Master's degree 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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Deep expertise in data mining, statistical analysis, machine learning, and predictive modeling. Leverage predictive modeling and machine learning to forecast trends and customer behavior.
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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. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
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We are a multidisciplinary team with expertise in machine learning, data engineering, and software development. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Mgr, Machine Learning Engineering.
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The A12 team is an elite machine learning group strategically located within the CTO office of JP Morgan Chase which tackles business critical priorities using innovative machine learning techniques and technologies with a focus on machine learning for Software, Cybersecurity and Technology Infrastructure.
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Our group provides break-through AI solutions within legal, tax and government domains partnering with product managers, software engineers and subject matter experts using Natural language processing (NLP), Information extraction (IE) and Machine Learning (ML) techniques.
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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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Work with the latest technologies : You'll gain exposure to a broad spectrum of IoT, SaaS and machine learning obstacles, including distributed fault-tolerance, device control optimization, and process modeling to support scalable interaction with disparate downstream APIs.
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machine learning jobs Title: expert in New York, NY
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