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The successful candidate will bring experience as a data scientist and machine learning leader working for a company where "AI" is considered core to the company's success. Serve as a strategic leader as part of our data science & machine learning team, with responsibility for Xometry's pricing strategy.
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Reporting to Dr. Beam, the Research Assistant (RA) will support the development of Cria, an open-source AI system designed for neonatology, by contributing to machine learning and data science research efforts.
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Strong familiarity with topics of protein and macromolecular structures and interactions with other proteinsExperience with cloud environments such as AWSExperience in developing machine learning platforms using modern ML frameworks for deep learning (, tensorflow, keras, MXNet) & deploying in services such as Amazon Sagemaker.
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Stay abreast of latest AI trends and maintain state-of-the-art knowledge in machine learning, deep learning, and computational linguistics. Experience with machine learning techniques and tools including deep learning, reinforcement learning, and unsupervised learning.
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Experience in crafting and utilizing machine learning algorithms, with a bonus for those familiar with biological or chemical data. Craft and implement machine learning models like graph neural networks and 3D convolutional networks, turning vast biological data into actionable insights.
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Create and implement mathematical models and machine learning algorithms for processing big data and extracting valuable insights. Familiarity with machine learning libraries such as scikit-learn, Tensorflow, PyTorch, Keras, etc.
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Expertise in scientific programming languages (e.g., Python, R) and machine learning libraries (e.g., PyTorch, Tensorflow) We seek an enthusiastic and collaborative machine learning scientist with a focus on AI/ML methods to join our Small Molecule Drug Discovery team.
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This person will work closely with colleagues from both the proteomics and the computational sciences teams to identify opportunities to apply data analytics and machine learning techniques to enhance Matchpoint's technology platform by contributing to both our chemoproteomics platform and our drug discovery pipeline.
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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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The ISR Division's projects focus on advanced signal processing, adaptive sensor technologies, advanced algorithms, machine learning, and modeling and simulation for applications that include airborne radar, electronic warfare, and undersea systems.
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Publications or blog posts displaying excellent writing on data science or machine learning topics. You will collaborate with company advisors from MIT and Harvard whose expertise span machine learning, medical imaging, and getting products successfully through FDA. We are looking for an individual with an exceptional Machine Learning background and track record of proven delivery who is not shy to take on extensive responsibilities.
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As a Machine Learning Engineer, you will collaborate with data scientists, product managers, and data engineers to operationalize machine learning models in production and manage the lifecycle of artificial intelligence algorithms on a variety of domains.
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Expert at Apache Spark, Databricks, Hadoop, or other big data systemsExperience with machine learning frameworks such as Scikit-learn, SparkML, MLFlow, KubeFlow, etc. 8+ years experience working with machine learning models and deploying them into productionDegree in Computer Science, Electrical Engineering, Data Science, or other related computational fieldsExperience with NLP, computer vision, or deep learning frameworks such as Tensorflow, PyTorch, or HuggingFace, etc.
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Masters or Ph. D. with experience in Machine Learning/Statistics/Data Science Experience with traditional as well as modern machine learning/statistical techniques, including NLP algorithms, LLMs, and quantization strategies.
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The team leverages its experience in the fields of signal processing, computer vision, computational linguistics, machine learning, artificial intelligence, communication systems, and other areas of electrical engineering and computer science to create impactful solutions.
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