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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Certified AWS Cloud Practitioner, Developer or Solutions Architect strongly preferred.
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Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training. Strong working knowledge of deep learning, machine learning and statistics.
$239,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Must have hands-on expertise in Cloud Computing (Azure, AWS), Big Data Processing using Oracle, Hadoop/HBase/Kafka/Spark of Data Platforms. Have 20+ years of hands-on Data Architecture, Data Warehousing, Data Analytics, Machine Learning, preferably designing & delivering a highly scalable application, and/or support vendor platforms to service the business needs.
$225,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Utilize a broad stack of technologies like Python, Pytorch, HuggingFace, LangChain, Spark, Kubernetes, Docker, AWS Cloud, Github etc., for model development and deployment. As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Certifications in AI, ML, or cloud computing (e.g., Google Cloud AI Engineer, Microsoft AI Engineer, AWS Machine Learning). Experience with cloud-based environments (AWS, Azure, Google Cloud) for AI deployment.
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Hands-on experience with cloud platforms (AWS, Azure, Google Cloud) and containerization technologies (Docker, Kubernetes). Experience with machine learning and data analytics.
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Experience working in cloud environment, preferably AWS using tools such as EMR/Spark, Kafka, Databricks, S3, EC2. Some knowledge of Data Science/Machine Learning. We are looking for a hands-on Data Engineering manager to play a key role in expanding the risk and fraud mitigating capabilities in our New York City office.
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Expertise: Deep expertise in AI, machine learning, deep learning, and natural language processing, with hands-on experience in building production-grade models and systems.
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AWS cloud services and technologies (i.e., Lambda, S3, DMS, Step Functions, Event Bridge, Cloud Watch, RDS) Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics.
$174,800 a yearFull-timeExpandApply NowActive JobUpdated 26 days ago - UpvoteDownvoteShare Job
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Strong data science and data engineering background both with open source and cloud distributed machines learning and AI tools especially Azure Cognitive Services, Azure Machine Learning and AWS Sagemaker and Bedrocks.
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Experience: Proven experience as a Machine Learning Engineer or similar role, with hands-on experience in developing and deploying machine learning models. Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) is a plus.
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Hands-on experience with deploying and managing solutions on Azure infrastructure; other cloud-native platforms like AWS and GCP are also acceptable. Skills- Python, UiPath, TensorFlow (Machine Learning.
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Hands-on experience with AWS cloud platform and knowledge of AWS data-related services including machine learning and artificial intelligence capabilities. Partner with data scientists to enable advanced analytics and machine learning capabilities.
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Hands on experience with microservices architecture, and cloud-native application development, hands-on experience developing in AWS Cloud Platform (ECS, EKS, MSK, Lambda, S3, RDS Aurora.
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