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Advanced Machine Learning Professional
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pushkar, India beBeeMachineLearning Full timeJob OverviewAs a machine learning engineer, you will be responsible for developing and deploying AI models to solve real-world problems.Main ResponsibilitiesDesign and develop machine learning algorithms using Python and relevant libraries such as NumPy, pandas, and scikit-learn.Experience with AI/Machine Learning frameworks such as TensorFlow and...
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pushkar, India beBeeMachineLearning Full timeSenior AI/ML Engineer PositionA cutting-edge Senior AI/ML Engineer is sought to spearhead the development of high-performing machine learning applications in cloud environments. The ideal candidate will have 6-8 years of experience in delivering production-ready code, accompanied by a deep understanding of ML/AI concepts and cloud architectures.Key...
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pushkar, India beBeeMachineLearning Full timeMachine Learning Operations ExpertWe are seeking a seasoned professional to design, develop, and manage scalable machine learning operations.Pipeline DevelopmentCreate efficient ML pipelines for training, validation, deployment, and batch/real-time inference using workflows and jobs.Implement distributed training and inference pipelines using PySpark and...
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Python Expert for Machine Learning
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pushkar, India beBeePython Full timeMachine Learning DeveloperWe are seeking an experienced Machine Learning developer to join our team. The ideal candidate will have a strong background in Python and machine learning algorithms.Job Description:The selected candidate will be responsible for developing and implementing machine learning models to solve complex business problems. This will...
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Data Driven Machine Learning Expert
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pushkar, India beBeeMachineLearning Full timeJob TitleWe are seeking an experienced Machine Learning Engineer to join our team and help drive the development of our large-scale machine learning platform.The ideal candidate will have a strong background in building, deploying, and maintaining AI/ML systems.Key responsibilities include designing and implementing data pipelines using Databricks and...
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Remote Machine Learning Freelancer Wanted
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Freelance Machine Learning Engineer
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pushkar, India Leading MNC Full timeLooking for a Freelance Machine Learning Engineer to join a team of rockstar developers. The candidate should have a minimum of 10+ yrs. of experience.There are multiple openings. If you're looking for freelance/ part time opportunity (along with your day job) & a chance to work with the top 0.1% of developers in the industry, this one is for you You will...
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Machine Learning Innovation Lead
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pushkar, India beBeeArtificial Full timeKey Responsibilities:Develop and enhance an open-source platform that incorporates AI capabilities to drive insights across enterprise environments.Collaborate with cross-functional teams to ensure the scalability, reliability, and deployment of ML models in production.Design and manage data pipelines using Databricks and related tools to streamline...
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pushkar, India beBeeMachineLearning Full timeJob OpportunityA forward-thinking organization seeks a skilled software developer proficient in the MERN stack with expertise in Machine Learning.Proficiency in the MERN stackHands-on experience integrating ML models/services into production environmentsFamiliarity with cloud platformsAbility to design and develop reliable, scalable software solutionsStrong...
Machine Learning Engineer
2 weeks ago
Project Description:We are seeking a skilled Machine Learning Engineer to develop and deploy Graph Neural Network (GNN) based surrogate models that approximate complex physics simulations for oil & gas pipeline and well networks. This is a hands-on role for someone who can build high-fidelity neural network models that replace computationally expensive reservoir and network simulators (Nexus, Prosper).Responsibilities:Design and implement Neural Network architectures to model flow dynamics in interconnected pipeline networksBuild surrogate models that accurately predict pressure distributions, flow rates, and network behavior under varying operational scenarios (training data is acquired through running simulations of the physics models)Create data pipelines to extract network topology and simulation results from physics-based models (Nexus/Prosper) and transform them into graph representationsDevelop training frameworks that incorporate physics constraints (conservation laws, pressure-flow relationships) into neural network loss functionsCollaborate with petroleum engineers to ensure model predictions align with physical behavior and operational constraintsImplement model monitoring, validation, and continuous improvement workflowsbusiness trip to KuwaitMandatory Skills Description:Strong expertise in Graph Neural Networks (GCN, GraphSAGE, Message Passing Networks) with proven implementation experienceDeep understanding of deep learning frameworks (PyTorch Geometric, DGL, or TensorFlow GNN)Experience building surrogate models or physics-informed neural networks (PINNs) for engineering applicationsProficiency in Python and scientific computing libraries (NumPy, SciPy, Pandas)Demonstrated ability to work with complex data structures (graphs, time-series, spatial data)Understanding of optimization techniques and handling large-scale training dataTechnical Domain Knowledge:Understanding of graph theory and network analysisExperience with data structures and graph representations (adjacency matrices, edge lists, sparse tensors)Knowledge of hyperparameter tuning, model building and uncertainty quantification in ML modelsNice-to-Have Skills Description:Background in petroleum engineering, process engineering, or fluid dynamicsFamiliarity with reservoir simulation or pipeline hydraulicsExperience with MLOps practices and model lifecycle managementPublications or open-source contributions in graph MLExperience deploying ML models in production cloud environments (containerization, API development)Industry Experience:Oil & gas industry experience is a strong plus, However, candidates with relevant surrogate modeling experience from other engineering domains encouraged to applyEducational Background:MS/PhD in Computer Science, Computational Engineering, Applied Mathematics, or related field preferredStrong mathematical foundation in linear algebra, graph theory, and numerical methodsUnderstanding of graph theory and network analysis
