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Proficient in statistical modeling, machine learning, and data science, particularly as applied to chemical and electrochemical systems. We aim to accelerate the sustainable energy transition by integrating artificial intelligence with material science.
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As a Machine Learning Engineer, you will play a critical role in the development, deployment, and optimization of machine learning models with a strong emphasis on large language models (LLMs) and MLOps.
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Prior exposure to validation or development of BSA/AML models, Fair Lending models, or Artificial Intelligence and/or Machine Learning models within a Financial Institution.
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Science or a related field plus one (1) year of experience as a Data Analyst or a related occupation performing advanced analytics using predictive modeling and machine learning algorithms.
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The ideal candidate will have a robust background in data science, machine learning, bioinformatics, and specific expertise in DNencoded library (DEL) machine learning and small molecule drug discovery.
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Experience with DevOps practices and tools for machine learning model deployment. As an ML Engineer, you will lead the development and deployment of innovative approaches to optimize existing and new machine learning systems, unlocking their full potential to drive maximum business value.
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Stay abreast of the latest advancements in AI, machine learning, and computational biology, and apply these insights to drive the company’s research agenda. As the Principal Machine Learning Scientist, you will be the driving force behind the AI initiatives that propel the company’s innovative drug discovery platform.
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Work at the intersection of experimental and groundbreaking digital technologies, with a particular emphasis on expertise in machine learning and artificial intelligence (AI) as applied to small molecule drug discovery.
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Machine Learning : Proficient in Machine Learning, NLP, or deep learning using Python. Machine Learning : Experienced in Machine Learning, NLP, or deep learning using Python.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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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. PhD in Computer Science, Artificial Intelligence, Computational Linguistics, or a related field.
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Analyze and gather input in areas including information retrieval, distributed computing, large-scale system design, networking, and data storage, security, artificial intelligence, natural language processing, UI design, and mobile.
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We're driving the company's digital transformation and modernization initiatives and expanding business capabilities using industry best practices and advanced technologies such as cloud, artificial intelligence and robotics process automation.
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For methods builders we also welcome links to github/bitbucket pages, and relevant bioinformatics/computational biology/machine learning community contributions. PhD in a relevant subject area (Computational Biology, Population Genetics/Genomics, Bioinformatics, Biostatistics.
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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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