Hire remote machine learning engineers near Atlanta or in a similar time zone
Keyvis Damptey
Freelance Machine Learning Engineer
Keyvis uses statistics and mathematics to discover valuable information by identifying, testing, and verifying relationships between all the factors influencing your business. This process unveils the nuances to the "lay of the land" when it comes to the costs, operations, or customer sentiment that your organization must work with. From there, you both can discover the impact of actions and design strategies around your organization's goals.
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Hameed Hasan
Freelance Machine Learning Engineer
Hamid is a data scientist with a Ph.D. in computer science/bioinformatics, with a minor in machine learning. He has a strong background in deep learning, algorithms, and programming. His past works have focused on designing predictive models both in industry and academia. His expertise lies in the healthcare domain.
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Jonathan Rhone
Freelance Machine Learning Engineer
Jonathan is a full-stack engineer who's as comfortable working on large-scale distributed systems as he is on client-facing single-page web apps. Jon also excels at working with big data, and has frequently worked on a petabyte scale.
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Dan Napierski
Freelance Machine Learning Engineer
Dan is a software architect and technology professional focusing on applications of blockchain technologies. He has years of experience providing professional consulting services to clients ranging from startups to global corporations. He specializes in bringing rigorous testing and bulletproof code to tough engineering challenges. He has deep expertise in many aspects of artificial intelligence, blockchain, machine learning, and automation.
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Lee Lin
Freelance Machine Learning Engineer
Lee graduated from MIT with Bachelor's and Master's degrees in Computer Science, Math, and Electrical Engineering. He has also obtained an MBA from Harvard Business School. With over 15 years of experience developing software for hedge funds, startups, and large software companies, he is excited to put his expertise to work for new clients.
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William Grisaitis
Freelance Machine Learning Engineer
William is a data scientist with a diverse background and skill set, having worked on deep learning, time series forecasting, Bayesian modeling, and more. He has co-authored academic research applying deep learning to computational neuroscience and has worked in industry applying machine learning to financial markets and consumer finance. William graduated from Duke University where he studied physics, finance, and literature.
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Pedro Henrique Rocha Moy
Freelance Machine Learning Engineer
Pedro is a hybrid data scientist-engineer with more than six years of experience building data processing pipelines and machine learning models. His specialties include big data, natural language processing, reinforcement learning, algorithmic trading, time-series analysis/forecasting, and numerical optimization. He's able to provide fully-automated and/or hybrid solutions meeting business needs in accuracy, transparency, and interpretability.
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Daniel Steinberg
Freelance Machine Learning Engineer
Daniel has an extensive background in machine learning dating back to 2011. He works with clients to fully optimize their products by vastly improving accuracy and speed, and develop tools for better predicting and testing. He is currently a part-time Ph. D. student researching artificial intelligence.
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John Muchovej
Freelance Machine Learning Engineer
John is a recent computer and cognitive science graduate. He primarily works in deep learning, previously focusing on CV and NLP but now focuses on RL and uses ML to interrogate the brain. He's currently a researcher at MIT and Harvard and has been working as an AI engineer for two years—both on self-started projects as well as freelance. He also spends some of his weekends teaching to undergraduate and high school students.
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Brian Todd
Freelance Machine Learning Engineer
Brian is an experienced data scientist and machine learning engineer with a track record of researching and deploying a wide range of models for natural language processing (NLP) tasks, computer vision algorithms, classical machine learning algorithms, Bayesian statistical models, time series analysis models, and large-scale data mining algorithms.
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