Senior Machine Learning Engineer (Healthcare) play a crucial role in any startup. It takes an extraordinary person to fulfil the Senior Machine Learning Engineer (Healthcare) role. We have selected these Senior Machine Learning Engineer (Healthcare)’s for this list as they are inspiring for a variety of reasons – whether that’s pushing boundaries, creating groundbreaking products, or doing their bit to save the world.
Our analysts did their best to select be best, and most innovative Senior Machine Learning Engineer (Healthcare)’s. The list is in no particular order!
Tempest van Schaik
Senior Machine Learning Engineer (Healthcare) @ Microsoft
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Tempest is a multi-disciplinary engineer, researcher and inventor. She has degrees in Biomedical Engineering, and in Electrical (Information) Engineering from University of the Witwatersrand (South Africa), and a PhD in Bioengineering from Imperial College London. She has experience in the end-to-end development of medical technology, from basic research to UX and product development, to building sensors, collecting data and using data science to understand human health. She has developed sensors to study the progression of cancer, low cost soil-nutrient tests for farmers in developing countries, phone and watch games which measure cognitive function in people with depression, and a low-cost device to measure ocean ecology. In her current role as a software engineer at Microsoft (UK), she applies machine learning to solve real, diverse problems in business and government, using a creative and multi-disciplinary approach.
Learn more about Tempest van Schaik on Crunchbase… Read more about Microsoft on Crunchbase…
Kostas Perifanos
Lead Machine Learning Engineer @ Argos
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Kostas joined Argos in 2017 as a Lead Machine Learning engineer. Prior to Argos, he worked at Royal Mail, Mailonline, Pearson and in research; he was involved in a broad range of projects from European FP6 research programs to EdTech, Analytics, Search, Predictive Modelling using Machine Learning and AI. He is interested in Deep Learning, Distributed Computing, Optimisation, Search, Predictive Analytics and Natural Language Processing.
Learn more about Kostas Perifanos on Crunchbase…Argos is a British online retail store that offers a range of consumer products in the U.K. and Ireland. Read more about Argos on Crunchbase…
Damien Lefortier
Machine Learning Engineer & Tech Lead @ Meta
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Damien Lefortier is a machine-learning engineer on the Ads Ranking team at Facebook. Previously, Damien worked on the core Machine Learning team at Criteo, where he helped improve Criteo’s predictive algorithms for ad targeting, and on the Search team at Yandex, where he focused on search quality and infrastructure. He is working toward a PhD in information retrieval at the University of Amsterdam. His research work has been published at top tier conferences, such as WWW and CIKM.
Learn more about Damien Lefortier on Crunchbase… Read more about Meta on Crunchbase…
Huma Lodhi
Lead Machine Learning Engineer @ Sky UK
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Sky is an entertainment company, serving 22 million customers across satellite, OTT, and broadband in five countries. Read more about Sky UK on Crunchbase…
Alejandro (Sasha) Vicente Grabovetsky
Machine Learning Engineer @ Apple
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Read more about Apple on Crunchbase…
Victor Zabalza
Machine Learning Engineer @ Faculty Science
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Víctor has a background in high-energy astrophysics, with ten years of research experience during which he studied the origin of gamma-ray emission from systems within our Galaxy. He is a data engineer at ASI Data Science.
Learn more about Victor Zabalza on Crunchbase…Faculty provides data science and engineering training services. Read more about Faculty Science on Crunchbase…
Kenneth Koski
Machine Learning Engineer @ Canonical
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Kenneth Koski is a machine learning engineer at Canonical with a focus on providing a scalable platform for ML workflows in Kubernetes. As far as a session description goes, this is my first time attending/presenting at SCaLE. Are you able to tell me what exactly is involved in a workshop, as opposed to a regular presentation? I think that might affect my session description.
Learn more about Kenneth Koski on Crunchbase…Canonical is a computer software company that markets commercial support and related services for Ubuntu and related projects. Read more about Canonical on Crunchbase…
Rivo Laks
Machine Learning Engineer @ Veriff
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Read more about Veriff on Crunchbase…
Alexis Boukouvalas
Head of Machine Learning Engineering @ Secondmind
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Alexis is a senior machine learning engineer with 7 years experience working as a software engineer in the query processor Microsoft SQL Server team and 10 years research experience in statistics. He has published more than twenty cited peer-reviewed publications in developing novel statistical models and applying them in computational biology, psychology and other domains. Prior to Cambridge, Alexis has lived in the US and northern England. He loves strong coffee and is a keen cyclist.
Learn more about Alexis Boukouvalas on Crunchbase…Machine learning for automotive innovators Read more about Secondmind on Crunchbase…
Ollie Glass
Contract data scientist, machine learning engineer & data strategist @ Ollie Glass Ltd
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I help companies with data science and machine learning from strategy to build. My work spans data science, engineering, product and business. Clients include venture-backed startups funded by Index Ventures, Balderton Capital, BGF and other top investors. If you’re looking for a data scientist, if you have a project in mind or want to explore ideas, feel free to get in touch.
Learn more about Ollie Glass on Crunchbase…Data science, machine learning & data strategy Read more about Ollie Glass Ltd on Crunchbase…
Remi Francis
Machine Learning engineer @ Speechmatics
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Powering applications that require mission-critical, accurate speech recognition Read more about Speechmatics on Crunchbase…
Chris Hughes
Machine Learning Engineer @ Marks & Spencer
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Demand is higher than ever to create and use Machine Learning models in production systems. However, community attention is usually focused on the process of building and training a model; with little acknowledgment given to how these models are then deployed and used by applications, and the supporting infrastructure required. I shall detail a case study of the processes and tooling used to successfully integrate ML into M&S’s Try Tuesday online personal styling service; from inception to deployment. This talk will be useful for anyone wishing to utilise ML models into production systems in a robust and scalable way. Chris is a machine learning engineer with interests in Deep Learning, Game Theory and Systems Architecture design; having obtained a BSc Mathematics and MScComputer Science from the University of York. Chris currently works for M&S’s Try Tuesday online personal styling service; encompassing projects such as fashion relevant visual search, customer segmentation and targeted recommendations. Outside of industry, Chris has authored award-winning research papers on the application of extortion strategies to the iterated poisoners dilemma, and utilising the Monte Carlo tree search algorithm to create the first successful opponent model for the game Liar’s Dice.
Learn more about Chris Hughes on Crunchbase…Marks & Spencer, through its subsidiaries, engages in retailing clothing, food, and home products. Read more about Marks & Spencer on Crunchbase…
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