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Extensive experience with Python Machine Learning toolsets (Tensorflow, PyTorch, Scikit-learn, Numpy, Pandas) 10+ years of professional experience as a data scientist or machine learning engineer with proven track record of delivering functional product oriented ML solutions.
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Expert knowledge of Python programming and machine learning frameworks (Scikit-learn, TensorFlow, Keras, PyTorch, etc.) Extensive experience in at least one cloud platform (e.g. AWS, GCP, Azure) and associated machine learning services, e.g. Amazon SageMaker, Azure ML, Databricks.
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Advanced knowledge of math, statistics, multivariate analysis, statistical tests Advanced Python coding skills Experience with one or more machine learning frameworks such as TensorFlow and/or PyTorch Understanding of numerical implementations Understanding of cloud computing Knowledge of data querying knowledge of EMG, EEG, ECG, IMU, CV algorithms Experience with C.
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We are seeking a machine learning engineer to work closely with our product and research teams to develop SOTA deep learning software. Solid knowledge of machine learning and deep learning fundamentals with experience in one or more of computer vision, NLP, speech, reinforcement learning, generative models, etc.
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Proven experience as a machine learning engineer or similar role. Strong programming skills with proven experience implementing Python-based machine learning solutions. Collaborate with research and product development teams to build machine learning products.
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The ideal candidate has a machine learning background, with previous experience building large-scale generative models, complex pre-processing pipelines, and comprehensive benchmarks to support scientific tasks.
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Solid understanding of machine learning methods, ideally deep learning, with experience using at least one of the following frameworks: Pytorch, TensorFlow, JAX. The Karczewski Laboratory in the Center for Genomic Medicine (CGM) and Analytic and Translational Genetics Unit (ATGU) at Massachusetts General Hospital (MGH) and the Broad Institute of Harvard and MIT is seeking exceptional computational biology candidates to build tools necessary to visualize and interpret massive data sets of human genetic variation and functional genomic information.
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Familiarity and/or willing to learn deep learning capabilities leveraging Tensorflow/Torch. Familiarity and/or willing to learn deep learning capabilities leveraging Tensorflow/Torch.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. Knowledge of and experience with signal processing, time-series analysis, biosensor systems, and analyzing biomedical dataAcademic research experience in DL and ML with published articles or minimum of 2 years of industry experience with focus on DL/ML algorithmsProficient in Python, and familiar with ML/DL libraries like scikit-learn, Tensorflow, PyTorch, Keras, etc.
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Pfizer Worldwide Research, Development, and Medical (WRDM) is expanding its work in applying Machine Learning (ML) and Artificial Intelligence (AI) technologies to Biomedical Research. The centerpiece of this initiative is the establishment of a "ML Research Hub," a new group charged with mastering state-of-the-art machine learning techniques to create novel predictive models and tools used across WRDM. Data Engineering will be key to the success of this new group given the enormous scope of the chemical, biological, omics, and clinical data available at Pfizer.
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Possess deep functional and technical understanding of the Machine Learning technologies (Googles Cloud Platform, custom and COTS-embedded) and provide prescriptive guidance on how these are leveraged across the Fuse landscape.
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Strong knowledge, experience, and fluency in a wide variety of tools including Python with data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), Spark, SQL; familiarity with Alteryx and Tableau preferred.
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Analytical needs can include: data aggregation / creation, data cleaning / manipulation, commercial data science (e.g., geospatial, machine learning, predictive modelling, NLP, GenAI etc.
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The WRDM Research Hub is seeking experienced data engineers with a background in machine learning, software engineering, technical problem-solving skills, and experience in creating scalable data pipelines and infrastructure for training, validating, and deploying into production ML solutions for broad usage.
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Python Development: Have a minimum of 3-5 years of hands-on experience in Python development, with a particular focus on data science, machine learning, and AI. Moreover, at least 4-8 years of experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and proficiency in other Client algorithms and libraries.
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