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Key Responsibilities:- Design, develop, and deploy advanced machine learning models and algorithms, leveraging deep learning frameworks such as PyTorch and TensorFlow. - Extensive experience with machine learning frameworks like PyTorch and TensorFlow.
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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. Strong programming skills in Python, and familiarity with AI frameworks like TensorFlow or PyTorch.
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Experience in building, deploying, maintaining and sunsetting large-scale machine learning models and systems in production environments using TensorFlow, Keras, PyTorch, Scikit-Learn, AWS, Azure, Google Cloud.
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Strong fluency in Python and SQL, experience with Tensorflow, PyTorch, Airflow and data warehouse. Strong experience with Python/R, forecasting methodologies, machine learning and statistics.
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Xometry is an on-demand manufacturing marketplace that leverages machine learning (ML) techniques to predict the manufacturing cost of machined parts and produce automated buy it now prices on Xometry.com. Customers love our instant quoting engine, and that engine depends on Xometry’s ML team and technology.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow. These efforts have resulted in making machine learning more accessible to teams at Waymo, including Perception, Behavior Prediction, Planner, Routing, Maps and Research, ensuring greater degrees of consistency and repeatability, and addressing the "last mile" of getting models into production and managing them once they are in place.
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Deep learning frameworks such as TensorFlow, Keras, Torch, Theano. Expert level of understanding of NLP, NLU and Machine learning/Deep learning methods. Do applied research on a wide array of text analytics and machine learning projects, file patents and publish the papers.
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Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modelling platforms such as Azure AutoML, SageMaker, DataBricks, DataRobot, and H2O.ai.
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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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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Hands-on experience with deep learning frameworks such as Jax, PyTorch, Tensorflow. PhD degree in Computer Science or a similar discipline, or an equivalent amount of deep learning experience.
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Experience in statistical learning methods for GTM attribution and building from the ground up end-to-end data driven attribution systems which may include marketing mix models (MMM) and algorithmic multi-touch attribution (MTA.
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This exciting opportunity offers the chance to leverage your expertise in Python and machine learning libraries like TensorFlow, PyTorch, and Scikit-learn to drive innovation and solve complex data science challenges.
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Technical Skills: Proficiency in AI and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. Experience: Minimum of 3-5 years of hands-on experience in AI and machine learning development, with a proven track record of delivering AI solutions.
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