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Expertise in NLP and machine learning frameworks (e.g., TensorFlow, PyTorch). Azure Cloud AI Engineer (Chatbot) Minimum of 5 years of experience in cloud infrastructure design and management, with a strong focus on Microsoft Azure.
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Experience with other deep learning frameworks (e.g., TensorFlow, Keras). Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and their machine learning services. At IBM, we pride ourselves on being an early adopter of artificial intelligence, quantum computing and blockchain.
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Tensorflow), Lightbend (Akka, Scala), Hashicorp, Datastax (Cassandra, DSE Graph), Confluent (Kafka), and Databricks (Spark, Delta Lake), etc. Experience on Azure cloud, Azure DevOps and various services available on Azure.
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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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Experience with machine learning algorithms and frameworks such as TensorFlow, Keras, PyTorch, Scikit-Learn, Knowledge of cloud computing platforms such as AWS, Azure, Google Cloud. With Cash App, anyone can easily send, spend, or invest their money in stocks or Bitcoin.
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Understanding of machine learning concepts and experience with ML platforms like Azure Machine Learning or TensorFlow. Proficiency in Microsoft Azure cloud services, including Azure Data Factory, Azure Databricks, Azure SQL Database, Azure Data Lake, etc.
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5+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow, PyTorch and LangChain with GPU and CUDA experience being extremely advantageous.
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Expertise with LLMs (Microsoft Azure Open AI, AWS Bedrock and other LLM models) Experience working with machine learning algorithms such as Scikit-Learn, TensorFlow, PyTorch, MXNet, etc.
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API platforms such as Postman, Azure API Management or Boomi. SciKit Learn, TensorFlow, Pytorch,XGBoost and NLP libraries. As a Machine Learning Engineer, Openings Studio, you will roll up your sleeves to help us discover new and interesting ways to make our users lives faster and easier than ever before, leveraging both traditional machine learning techniques and Large Language Modeling (LLM) and Generative AI solutions.
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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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Machine Learning : Tensorflow, Scikit learn, Kubeflow, Machine Learning : Dataiku, Azure ML, SageMaker, VertexIA, Databricks ML, Azure Cognitive Services, ML Framework (TensorFlow, Keras, PyTorch.
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Experience with cloud data warehouses (Snowflake, AWS Redshift, Google BigQuery, Azure Data Warehouse, Databricks Lakehouse, etc.) Expertise across modern cloud AI platforms (Databricks, Snowflake, AWS SageMaker, Azure ML, GCP Vertex AI, Dataiku, etc.
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Apache Spark AWS AI Services AWS S3 AWS SageMaker Azure Cognitive Services Azure DevOps Azure Machine Learning Dataiku GCP Vertex AI Vertex AI. Experience with ML deep learning TensorFlow PythonNLP.
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AI/ML workloadsPerformance benchmarking Hardware accelerators and specialized devices (GPU, HPU, HPC) Git development workflowKubespray, Kops, or Kubadm Preferred Qualification:Slurm, Volcano, MPI, PyTorch, TensorFlow or other schedulers and AI domain frameworksOn-premises data center networkingCloud development or architecture (AWS, GCP, Azure, etc.
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Strong expertise in generative AI techniques for summarization, Chatbot and data embedding using AWS, Microsoft Azure Open AI and other open source LLM models. Hands-on experience of machine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, ML and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and ML techniques.
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