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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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A Glimpse into the Daily Routine of a Machine Learning Engineer. The Data Engineer builds pipelines that are used to transport date from a data source to a data warehouse. 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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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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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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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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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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Kensho is a Machine Learning (ML) and Natural Language Processing (NLP) company, centered around providing cutting-edge solutions to meet the challenges of some of the largest and most successful businesses and institutions.
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Have expertise in Machine Learning best practices (e.g. model evaluation and hyperparameter tuning, A/B test, feature engineering, feature/model selection), algorithms (e.g. gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g. natural language processing, computer vision, personalization and recommendation, anomaly detection.
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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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We are looking for a motivated and quality-focused Senior Machine Learning Engineer to play a critical role in deploying and maintaining machine learning models to drive business outcomes.
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Experience with advanced machine learning techniques, including LLM and generative AI for generating high-quality metadata and artwork. Develop and implement advanced machine learning techniques, such as LLM and generative AI, to generate high-quality metadata and artwork for content on the platform.
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You have successfully partnered with Product, Data Engineering, Data Science and Machine Learning teams on strategic data initiatives. Modernize Signifyd’s Machine Learning (ML) Platform to scale for resiliency, performance, and operational excellence working closely with Engineering and Data Science teams across Signifyd’s R&D group.
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The mission of the Teaching + Learning Commons (the Commons) is to advance student success through teaching excellence and comprehensive academic student support; be an incubator for student academic success innovations; increase access to education on campus and beyond; and actively promote equity and inclusion within the organization and through its programs and services.
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This opportunity is for a Director, Software Development who will manage and grow one or more engineering teams for Audible’s Machine Learning Engineering (MLE) team. This opportunity is for a Director, Software Development who will manage and grow one or more engineering teams for Audible’s Machine Learning Engineering (MLE) team.
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As a subject matter expert, you will actively lead projects focused on aligning learning and development with the priorities of the business with the support of the Learning & Development Manager and Lead Associate.
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Title: machine learning engineer Company: Tinder in Newark, NJ
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