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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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The Data Scientist will conduct artificial intelligence and machine learning (AI/ML) research and development for a portfolio of NASA applications with focus on aeronautics projects such as Air Traffic Management, Aviation Safety, Sustainable Aviation, and/or Advanced Air Mobility.
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6+ years of relevant experience across machine learning engineering, software engineering, data scientist, or data engineering roles (3+ years in data and/or machine learning focused roles.
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As a Machine Learning Engineer at Nelnet, you'll be at the intersection of data science and software engineering. Feature Engineering: Collaborate with Data Scientists to engineer features for machine learning models.
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Our Machine Learning Engineer role is at the core of this transformation, creating intelligent systems that automate processes, derive insights, and enable us to make better decisions.
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Collaboration: Work closely with Data Engineers to ensure seamless data integration for machine learning models. You'll collaborate closely with Data Scientists, Data Engineers, and business stakeholders to bring machine learning solutions from conceptualization to production.
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This Scientist position will develop machine learning workflows for generative shape modeling from single cell image data. Scientist I Machine Learning for Generative Shape Modeling - Careers at Allen Institute Back To Openings Scientist I – Machine Learning for Generative Shape Modeling Department: CS - Computational Cell Science Start Your Application Scientist I – Machine Learning for Generative Shape Modeling.
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Scalability: Design and implement scalable machine learning pipelines using cloud-based solutions on platforms like AWS, leveraging tools such as Terraform for infrastructure management.
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Model Development: Create, validate, and deploy machine learning models using advanced algorithms and frameworks like TensorFlow, PyTorch, or scikit-learn. Bachelor's or Master's in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
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The Bioinformatics Scientist is responsible for analyzing antibody selection data from yeast display, implementing machine learning algorithms to enhance data analysis and lead selection, and managing the data pipeline from raw file processing to database storage.
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Familiarity with cloud platforms like AWS for machine learning solutions. Mentorship: Provide guidance and mentorship to junior team members in machine learning best practices.
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Utilize CI/CD pipelines to automate the deployment and maintenance of machine learning solutions. Strong understanding of machine learning algorithms and statistical. Hands-on experience with machine learning frameworks such as.
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Your primary focus will be on designing, building, and deploying machine learning models to solve various business problems. Proficiency in using CI/CD pipelines for automating machine learning work.
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Should have a strong background in at least two of the following areas: Algorithm Development, Machine Learning/AI and Data Analysis, Mathematical Modeling and Simulation, Digital Signal Processing, Control Algorithms Design.
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Minimum of 3 years of experience in machine learning engineering or. Experience in deploying machine learning models in production. If you're passionate about applying machine learning techniques to real-world challenges, we invite you to join our team and contribute to shaping the future of our business.
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