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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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As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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Hands-on experience in developing scalable data pipeline using technologies like Kafka, Databricks, Spark and Scala applying ETL and ELT concepts. 3+ years of hands-on experience in implementing data lake systems using AWS/Azure cloud technologies such as S3, Databricks, Hive.
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The candidate must have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.
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4- 8 years of experience as machine learning engineer/data scientist. Experience using machine learning libraries or platforms, including Tensorflow, Caffe, Theanos, Scikit- Learn,or ML Lib for production or commercial products.
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You should possess strong technical skills in SQL, Python, Spark, and PySpark and have hands-on experience with AWS and Databricks platforms. Strong understanding of distributed systems, and machine learning basics.
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By joining us as a Principal Machine Learning Engineer, Infrastructure (LLM), you will work on state-of-the-art systems, contribute to cutting-edge research, develop innovative algorithms, and play an essential part in Prescient Design's success.
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Hands on experience in dealing with structured and unstructured data from multiple sources and applying machine learning techniques and algorithms to discover patterns, intents and build knowledge repositories and graphs to solve enterprise problems.
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Along the way, you will gain hands-on experience in a face-paced environment that’s challenging, rewarding, and career-defining. 8+ years as an Electrical Engineer, Compliance Engineer, EMI Engineer, EMC Engineer, or related title preferred.
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4+ years of hands-on industry data science experience, using typical machine learning and data science tools including pandas, scikit-learn, gensim, nltk, and TensorFlow/PyTorch.
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Azure Platform Experience: The candidate should have hands-on experience with various Azure services including but not limited to Azure Data Factory, Databricks, Data Lake, and Power BI. They should be able to design, build, and maintain ETL pipelines, manage data lakes, and create insightful reports and visualizations.
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Demonstrated experience in applying advanced analytics techniques, including predictive modeling, machine learning, regression analysis and/or A/B Testing, to solve complex business problems.
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ML Ops: Design and Build customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domainsTechnical Expertise: Serve as the subject matter expert on AI technologies, including machine learning, natural language processing, computer vision, and other relevant domains.
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machine learning engineer hands on jobs Company: Jpmorgan Chase Co in New York, NY
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