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Deliver simple solutions to complex problems as a Machine Learning Engineer at GDIT. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. Our work depends on TS/SCI cleared Machine Learning Engineer joining our team to support our intelligence customer in Springfield, VA or St. Louis, MO.
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As a Machine Learning Engineer you will help ensure today is safe and tomorrow is smarter. Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
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Machine Learning Engineer, NeRF. The ideal candidate will have a strong background in computer vision, machine learning, and deep learning, as well as experience working with neural radiance fields.
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Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Machine Learning Engineering - Dallas, TX (Hybrid) Optimize machine learning algorithms and infrastructure for performance, scalability, and cost-efficiency. Deploy machine learning models into production environments, ensuring scalability, reliability, and real-time performance.
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We are actively seeking a Senior Machine Learning Engineer to contribute to innovative projects for a prestigious Global Financial Services organization. Key Responsibilities:- Design, develop, and deploy advanced machine learning models and algorithms, leveraging deep learning frameworks such as PyTorch and TensorFlow.
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Digital Core Tech@Lilly is actively looking for an AI Machine Learning Engineer to spearhead our efforts in the development and deployment of machine learning models that enhance predictive analytics and decision-making across multiple processes and systems in pharma.
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At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.
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Clean, preprocess, and transform raw data into a suitable format for machine learning models. Collaborate with data scientists, software engineers, domain experts, and client stakeholders to understand requirements, gather feedback, and integrate machine learning solutions into larger systems or products.
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Topics of specific interest include: (i) decision making under uncertainty / optimal design and control of experiments and physical or biological systems; (ii) uncertainty quantification for physical or biological systems or machine learning; (iii) optimization; (iv) model reduction / digital twins / surrogate modeling or emulation; (v) modeling & simulation; (vi) scientific machine learning; (vii) computational and experimental workflows and pipelines for science and engineering problems.
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Agility Partners is seeking a qualified Machine Learning Engineer to fill an open position with a Fortune 500 company based in the greater Connecticut area. As a Machine Learning Engineer, you will play a pivotal role in designing, building, and maintaining sophisticated machine learning models and pipelines.
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This team is specifically passionate about growing Oracle Cloud's HPC ecosystem, see OCI has a leading solution for training and running large machine learning models. Zoom is using OCI to connect millions of people and Red Bull Racing leverages Oracle's machine learning capabilities to set new standards for Formula 1.
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PhD in Computational Biology, Computational Bioengineering, Machine Learning, Statistics, Computer Science, Mathematics, or a related field. Significant experience and advanced knowledge of developing and applying algorithms in one or more of the following machine learning areas/tasks: deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, transformer-based language modeling, multimodal learning, ensemble methods, scalable online estimation, and probabilistic graphical models.
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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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API Development & Deployment: Develop and implement APIs using Flask, FastAPI to deploy machine learning models and integrate them into existing systems or applications. Five or more years of industry experience in data science with a focus on data analytics, machine learning, and deep learning.
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machine learning jobs Title: devops engineer Company: Mission Technologies A Division Of Hii
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