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Having experience with computer vision, natural language processing (NLP) or large language model (LLM) is a plus. Having experience with productizing machine learning models within a cloud service (e.g., AWS, Azure, GCP) and data science environments (e.g., Databricks) is a plus.
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Our client, a leading oil and gas company, is looking for a Machine Learning Engineer to join their team. Experiment with various machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, reinforcement learning, and ensemble methods.
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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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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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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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As a member of the Data Engineering team, the Machine Learning Engineer will work closely with Business domain experts and Data Scientists to solve real-world oil and gas midstream problems using advanced analytics, machine learning, and artificial intelligence.
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Exhibit a deep understanding of the energy/commodity trading landscape, encompassing Oil, Gas, Power, LNG, or other commodities. In the US, we have operated for over a century and are a major oil and gas producer onshore and in the Gulf of Mexico, a recognized innovator in exploration and production technology, and a leading manufacturer and marketer of fuels, natural gas, and petrochemicals.
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Training in project management software and techniques including project scoping and estimating utilizing work breakdown structures, cost and schedule control systems, design and construction management, team building, resource planning, procurement, and permitting is a plus.
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GROWTH/INNOVATION ESSENTIAL FUNCTIONS Performs, trains, and mentors industry sterile processing standards i.e. Steam, ETO and Low Temperature Hydrogen Peroxide, while seeking opportunities to expand learning beyond baseline competencies with a focus on continual development.
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Requires three (3) years of experience in: (1) data analysis with Python and Python machine learning packages; (2) creating analytics tools to visualize KPIs in relation to equipment and process engineering; (3) MS Excel Macros and Pivot tables; (4) SQL, Tableau, and Spotfire; (5) knowledge of semiconductor process.
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Knowledge and experience using engineering design software such as HYSYS, GasCalc, Pipeline Toolbox, Caepipe, Caesar II, or similar is a plus. Have a working knowledge of compressor station, M&R, and facility design in accordance with PHMSA DOT Part 192.
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7+ years of direct sales experience carrying and exceeding a quota and selling enterprise software/ software-as-a-service (Business Intelligence/ Data Warehouse/ Big Data/ Advanced Analytics/ Machine Learning) to C-level executives.
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Enterprise Products Partners L.P. is one of the largest publicly traded partnerships and a leading North American provider of midstream energy services to producers and consumers of natural gas, NGLs, crude oil, refined products and petrochemicals.
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Plains All American is an industry-leading transportation and midstream provider specializing in transportation, storage, processing and marketing solutions for crude oil and natural gas liquids (NGLs.
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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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