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Extensive experience in at least one cloud platform (e.g. AWS, GCP, Azure) and associated machine learning services, e.g. Amazon SageMaker, Azure ML, Databricks. Strong understanding of fundamental computer science concepts, software design best practices, software development lifecycle and common machine learning design patterns.
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Must have a strong background in one or more of the following: Mathematical, Statistics, Probability, Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
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Azure/ AWS/ GCP certifications, AWS Machine Learning Specialty, Google Certified Cloud Engineer and Deeplearning.ai certifications on LLMs, prompt engineering. At least 5 years of extensive experience in Machine Learning algorithms development, Deep Learning ( should be an expert in Neural networks including but not limited to , ANN, CNN, RNN ( LSTM ( BiLSTM, GRU both.
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Develop and support cloud-based big data pipelinesUse analytics to understand product behavior and motivate data-driven decisions. Experience with data-intensive applications, big data pipelines and analytics, having used tools such as Snowflake, DataBricks, Amplitude and Looker.
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Train, tune and validate machine learning models using Tensorflow, python and GCP cloud infrastructure. Knowledge of programming and machine learning tools including Python, SciPy/NumPy/Pandas, TensorFlow, Git and cloud computing platforms.
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Our tenant is a strong cross-domain team to deliver E2E solutions covering tech areas ranging from machine learning, big data, microservices to data visualization. Build next-gen cloud based big data infrastructure for batch and streaming data applications, and continuously improve performance, scalability and availability.
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Hands on experience with modern cloud data warehouse and engineering for one or more of the following cloud providers - GCP (Big Query, Vertex, Cognitive Services), Snowflake, Azure (Synapse, Dynamo, Cosmos, Azure ML, Power BI), AWS (Redshift, Sage maker), Tableau.
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To further innovate and enhance our capabilities, the Lockheed Martin Rotary and Mission Systems (RMS) Systems of Systems Artificial Intelligence (AI) team is looking to recruit a Machine Learning Engineer based in Manassas, Virginia.
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As a Data Scientist, youll use your full toolkit statistical modeling, machine learning, data mining, data visualization, and software engineering to develop data products and models that are used by millions of users and power the growth of our business.
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Experience in building, deploying, maintaining and sunsetting large-scale machine learning models and systems in production environments using TensorFlow, Keras, PyTorch, Scikit-Learn, AWS, Azure, Google Cloud.
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We are looking for a senior Machine Learning Engineer with deep expertise in attribution space (just like you!) Additionally, we are dedicated to crafting exceptional data infrastructure and innovative solutions in the realms of data science and machine learning.
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Lead Software Engineer, Full Stack (Enterprise Data) Enterprise Data is hiring a Lead Software Engineer! At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud.
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We are a multi-faceted software development and systems administration team working to build and maintain software applications backed by a self-managed cloud infrastructure (OpenStack) with a true big-data footprint (over 10 petabytes.
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At Cognizant Digital Engineering, a small cross functional team comprised of a Product Manager, an Architect, Full-Stack Developers, UI/UX designers and Big Data analysts builds higher quality software faster siloed individuals working independently.
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Work in an agile environment with multidisciplinary teams, including software engineers, cloud engineers, machine learning engineers, data scientists/domain experts, UX/UI, front-end developers, scrums masters, product owners, and most importantly, USERS.
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