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Deep Learning, Red Hat OpenShift, Tensorflow. Demonstrated professional or academic experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) such as ResNet or U-Net for object detection or segmentation tasks using satellite imagery.
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Deliver simple solutions to complex problems as a Machine Learning Engineer at GDIT. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. Our work depends on TS/SCI cleared Machine Learning Engineer joining our team to support our intelligence customer in Springfield, VA.
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5-7 years experience across deep learning frameworks like Keras, TensorFlow or PyTorch and machine learning packages (sklearn, etc.) The ideal candidate has both a theoretical and practical understanding of deep learning techniques and has a proven track record in areas such as clinical research, computational biology, probability, statistics, or data science.
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Experience in big data technologies, e.g. Hadoop, BigQuery, MapReduce, Apache Spark. Solid understanding of foundational concepts and algorithms in statistics and machine learning, including NLP, linear/logistic regression, SVM, random forest, boosting, neural networks, dimensionality reduction, reinforcement learning, etc.
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Proficient in Databricks, Python, Pyspark, Scala for developing and maintaining data engineering pipelines, with expertise in Apache Spark, Flink, and containerization. Expertise in architecting, designing and building data pipelines and acquiring data needed to build and evaluate models, using tools like Databricks, Dataflow, Apache Beam, or Spark.
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Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
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We are hiring a talented Senior Data Engineer in roles related to building cloud-based data pipelines for machine learning, data processing with Apache Spark, and database development.
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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Apache Kafka, Apache Flink, Apache Spark, Trino (Presto), Apache Airflow/Dagster, Apache Superset, AWS S3, Snowflake, Amplitude, CDP (e.g. Segment.com) The adjacent areas of major focus are Machine Learning Infrastructure and workflow, Experimentation Platform, Knowledge Graphs and various Data Science and Analytics related tooling.
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Proficiency with deep learning tools and at least one machine learning tool, such as Hadoop, Apache Spark, TensorFlow, scikit-learn, or cloud-provider equivalents.
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Proven ability to work with at least one machine learning tool like Hadoop, Apache Spark, TensorFlow, or scikit-learn, or cloud-provider equivalents. Responsibilities and Contributions Organizational and Leadership Role Coaches and mentors others by example and through direct coaching on machine learning and artificial intelligence skills.
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3+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake, or Databricks for Data Engineering or Machine Learning workloads. The search team comprises the e-commerce search platform, backend services, machine learning endpoints, and our search engine, which enables grainger.com customers to findproducts that serve relevant content to online customers, internal support teams, and marketing programs.
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We are a well established Defense contractor with deep expertise in Machine Learning and Deep Learning projects for Military and Homeland Security programs. Defense industry leader in Machine Learning/Deep Learning programs - we are hiring for multiple roles in our Los Angeles HQ.
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Good understanding of machine learning, deep learning (including LLMs) and natural language processing and ability to optimize machine learning models to adapt to solving various kinds of issues.
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Proficiency in at least one of the following deep learning framework: TensorFlow or PyTorch. In-depth understanding of deep learning technology in recommendation system or NLP fields.
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