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We are seeking a highly motivated machine learning and AI Principal Scientist to join our Computational Tissue Imaging Research team in the Translational Bioinformatics organization. Strong coding skills in Python, and experience with machine-learning and deep learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, etc.
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4+ years of experience implementing and applying algorithms for machine learning and artificial intelligence. Proficiency with standard machine learning tools and frameworks: Python, PyTorch, Huggingface Transformers.
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As a Machine Learning Engineer, you’ll develop ML-based metrics for evaluating an autonomous vehicle system offline at large scale. Machine Learning development experience.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Master's Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science.
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Experience with building machine/deep learning models with at least one common framework such as PyTorch, Tensorflow, or JAX. Exciting Senior Machine Learning Engineer role with rapidly growing Biotech on the cutting edge of protein design.
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Our laboratory applies computational and machine learning methods to investigate the impact of seizures and abnormal brain activity on outcomes in pigs with cortical impact. The machine learning engineer will be responsible for data from the electronic data repository, including EEG, video, and peripheral blood biomarkers.
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We are seeking a skilled Machine Learning Engineer with expertise in Azure, Databricks, and MLflow, as well as strong full-stack capabilities, including experience with React. Experience with Azure cloud services, particularly Azure Machine Learning and Azure Databricks.
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PostEra is using machine learning, applied to medicinal chemistry, in order to expedite the discovery of new drugs and get new cures to patients faster. PostEra offers medicinal chemistry powered by machine learning.
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Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, and human data collection in laboratory and field environments.
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We are looking for a passionate, talented, and resourceful Senior Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas.
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Master's degree (or higher) (or foreign education equivalent) in Engineering, Statistics, Data 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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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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Postgraduate school experience in one or more of the following areas: bioinformatics, cheminformatics, computational chemistry and machine-learning. Apply machine-learning methods (e.g. deep learning, reinforcement learning, and generative adversarial networks) to biological imaging data to evaluate temporal and spatial effects of novel targets.
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San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Lead Machine Learning Engineer. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Lead Machine Learning Engineer.
$234,700 a yearRemoteExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Who You Are: You are a dynamic Computational Scientist who will work with other scientists to apply cutting-edge computation, Machine Learning/Deep Learning approaches to revolutionize our large molecule computational tools by contributing to accelerating and improving the process of design and engineering of novel biologics drug candidates.
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