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Use cutting edge technologies such as Python, Scala, Spark, and a variety of Cloud services to develop modern data pipelines supporting Machine Learning and Artificial Intelligence. As Data Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Eagle Bank. We are a place where we take pride in our low egos, value curiosity and learning.
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A deep understanding of data science and machine learning best practices, development processes, and leading platforms (Databricks, SAS, Anaconda, Alteryx, etc.) 2+ years’ experience in machine learning (ML), artificial intelligence (AI), and/or natural language processing (NLP) preferred.
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Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities. Deep Learning: Understanding neural networks, backpropagation, architectures like CNNs, RNNs, transformers, and tools like TensorFlow, PyTorch, or Keras.
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Demonstrated experience implementing machine learning models on text and multimedia data such as Spark NLP and Computer Vision models. Demonstrated experience with Apache Spark and managing Spark clusters.
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Expertise in advanced data science, machine learning, and artificial intelligence techniques, supported by a strong track record in programming languages such as Python, R, SQL, and proven software engineering methodologies.
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Experience with spark, scala, and databricks. A highly motivated data scientist, machine learning engineer, or experienced software engineer looking to transition into machine learning.
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In-depth knowledge of Apache Spark and Databricks architecture. Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks. This role requires a deep understanding of big data technologies, particularly Apache Spark, as well as expertise in data engineering and analytics.
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Experience with data engineering tools, including Databricks, Spark, Elasticsearch, Airflow, or a data warehouse. You'll develop algorithms, write scripts, build predictive analytics, apply ML and deep learning, and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help drive innovation, research, and development for our military and government leaders to make informed decisions.
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Experience with big data technologies such as Hadoop and Spark to efficiently process and analyze massive datasets. 3+ years of experience using Spark or PySpark. At Eagle Bank, you'll be part of a big group of makers, breakers, doers and disruptors, who solve real problems and meet real customer needs.
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3+ years of experience with distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) The Machine Learning Experience (MLX) team supports an internally hosted Model Training ecosystem running critical infrastructure for machine learning and data analysis across Capital One. You will get an opportunity to collaborate on the 1000's of models being trained on the platform by 4000+ users and dive deep into the unique engineering challenges we have around compute, data access, security and scale.
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You will work with tools like Snowflake, Spark, Kafka, Airflow and cloud data platforms to create robust data architectures and enable scalable and efficient data collection, storage, processing and analysis.
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Distributed Computing: Tools like Apache Spark, Hadoop. Transform your career to the next level with GDIT as a Solutions Architect where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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Experience with Machine Learning cloud technologies such as Azure Machine Learning (AML), AWS SageMaker or Spark ML. Experience with Big Data platforms such as Databricks or Apache Spark.
$82,000 - $236,500 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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4+ years of experience in machine learning engineering with production systems using Scala, Python, and Apache Spark. You will work with a variety of machine learning algorithms, from traditional models to cutting-edge LLM technologies, to address relevant problems.
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