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You also have opportunities to research and develop applications in applied artificial intelligence using computer vision, natural language processing (NLP) and large language models (LLM.
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The candidate should also have experience with multiple modern techniques and algorithms in machine learning and statistical computing such as regression, clustering/segmentation, time-series analysis, recommender systems, predictive analytics, Bayesian modeling, data fusion, supervised/unsupervised learning, decision trees, A/B testing, natural language processing.
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Deep understanding of deep learning architecture, machine learning, natural language processing (NLP), and generative models. Design and develop solutions that utilize generative AI, leveraging Machine Learning (ML) and Large Language Models (LLM), tailored to business needs.
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The Sr. Back Office Analyst will be responsible for a variety of activities related to physical and financial natural gas trading, including settlement of natural gas commodity invoices, natural gas pipeline and exchange statements, payment processing, reconciliations, trade confirmations, and reconciliation of data to ETRM system.
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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You must be familiar with image processing, machine vision, and data engineering, and even better if you are interested in 3D rendering, deep learning, and computer graphics.
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Our services include: natural gas gathering, treating, processing, transportation and storage; NGL transportation, fractionation, storage and import and export terminals; crude oil gathering, transportation, storage and terminals; petrochemical and refined products transportation, storage and terminals; and a marine transportation business that operates primarily on the United States inland and Intracoastal Waterway systems.
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A subsidiary of Veolia Group, Veolia North America (VNA) offers a full spectrum of water, waste and energy management services, including water, and wastewater treatment, commercial and hazardous waste collection and disposal, energy consulting and resource recovery.
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Bachelor's degree or higher in Environmental Studies, Planning, Geography, Civil or Environmental Engineering, Geology, or related natural resources science field of study. This is an excellent opportunity for an environmental professional looking to advance their career with a global environmental leader and expand ERM's team in the natural gas and LNG capital project delivery service line, with opportunities to support hydrogen, renewables, and carbon sequestration facility projects.
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Experience with big data technologies and frameworks, such as Apache Spark or Hadoop, enriching the skill set for handling large-scale data processing and analytics tasks. Data Engineering ManagerIntePros is searching for a dynamic Data Engineering Manager to join one of our local oil & gas clients here in Denver.
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That includes providing competitive compensation, professional development and a full benefit package: Medical/Dental/Vision Paid Holidays Vacation/Paid Sick Leave Voluntary Life Insurance 401K Telehealth Benefit covers all providers Maternity and Paternity Leave New Dads and Moms Benefit program Fertility Benefits Gender -Affirming Care POWER is a fun engineering firm.
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We are recruiting a Machine Learning Engineer for a major energy trader (energy / renewables). - Understanding of machine learning fundamentals, including deep learning, generative models, NLP techniques, such as sentiment analysis, and entity recognition and disambiguation.
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Familiar with data processing and visualization tools (SQL, Tableau, Power BI). Relevant certifications such as Microsoft Certified: Azure Data Scientist Associate or AWS Certified Machine Learning are advantageous.
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Versed in TensorFlow, PyTorch, scikit-learn, and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI). Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop.
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Previous OSP engineering and Field data collection experience, along with working knowledge of client software systems including, ARAMIS, BST-CAD, OSPCM, JMS (OPEDS), AOtX, AOTS, PLANET, CEEOT, MMT, PM Tool, EFACTS, MIC, LFACS, GRANITE and OCALC. The ideal candidate will have expert level experience with Customer Quality Control metrics, work print design, FTIs, and other measures to ensure first time acceptance.
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machine natural language processing full data engineering jobs in Houston, TX
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