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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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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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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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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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Utilize deep learning frameworks such as PyTorch and TensorFlow, as well as Python and R programming languages, to perform data analysis and software development relevant to the Cria project.
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Familiarity with machine learning libraries such as scikit-learn, Tensorflow, PyTorch, Keras, etc. A minimum of 2 years of industry or research experience in signal processing and/or machine learning.
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Experience with neural networks, deep learning, and reinforcement learning, using frameworks such as TensorFlow. 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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Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML etc. San Francisco, California (Hybrid On-Site): $213,400 - $243,500 for Lead Machine Learning Engineer.
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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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Strong programming skills in Python, with experience in deep learning frameworks such as TensorFlow, PyTorch, or Keras. Conduct research in machine learning, deep learning, and statistical modeling to design and implement new algorithms and techniques for multi-modal, generative AI, and LLM applications.
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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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We are seeking a machine learning engineer to work closely with our product and research teams to develop SOTA deep learning software. Experience with engineering and supporting ML pipelines in a popular ML framework such as PyTorch, TensorFlow, jax, etc.
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Familiar with deep learning platforms (e.g., Keras, Tensorflow) and related classification and segmentation algorithms. Applicants must have strong analytical, remote sensing and GIS skills and an exceptionally strong understanding of machine learning algorithms.
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Experience with TensorFlow, PyTorch, XGBoost, etc is a strong plusYou have experience with data pipeline tools like Apache Beam, Scio, etc., and cloud platforms like GCP or AWS. You routinely survey research publications in the machine learning and software engineering communities.
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Experience in the Design and implementation of AI/ML models and solutions using Google Cloud Platform technologies, including but not limited to Vertex AI , BigQuery, AI Platform, TensorFlow Extended (TFX), Dataflow, and Compute Engine.
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