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Work with the embedded Machine Learning Engineers on the team and ML platform services to deploy models to the production environment and monitor ongoing performanceUse Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, data platform and cloud services (both GCP & AWS) to get the job doneQualificationsYou Have: 5+ years of Machine Learning modeling experience.
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Our machine learning systems monitor and surface suspicious activity (money laundering, illegal activity and terms of service violations) for agent review. Work with the embedded Machine Learning Engineers on the team and ML platform services to deploy models to the production environment and monitor ongoing performance.
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As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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The Center for Ionomer-based Water Electrolysis (CIWE), an Energy Earthshot Research Center, has an immediate opening for a postdoctoral researcher to conduct applied research in the area of machine learning, pattern/feature detection, statistical description, computer vision, image processing and analysis, and parallel computing and will also be part of the Math for Experimental Data Analysis Group.
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Preferred Qualifications Familiarity with biological data formats, concepts, and computational models is a plus The salary range for Redwood City, CA: Staff Machine Learning Engineer: $232,900 - $315,100 The salary range for San Diego, CA: Staff Machine Learning Engineer: $221,000 - $299,000 Exact compensation may vary based on skills, experience, and location.
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Founded in late 2020 by a small group of machine learning engineers and researchers, Mosaic AI enables companies to securely fine-tune, train and deploy custom AI models on their own data, for maximum security and control.
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As a Senior Infrastructure Engineer on our Machine Learning Pod, you will lead the development and maintenance of our core machine learning infrastructure. Role Senior Software Engineer - Machine Learning, Infrastructure.
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Learn how to design scalable machine learning pipelines for data preprocessing, feature engineering, model training, and evaluation. As an Engineering Intern, you will join the Machine Learning Team in Winter 2025 to develop robust, well-designed products, implement new updates and features, and solve complex problems that affect our business and our clients.
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You will use our robust data and machine learning infrastructure to implement new ML solutions to make our consumer shopping journey delightful, fulfillment system efficient and knowledge graph accurate.
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5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day.
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Machine learning and data science is the core part of the company. Work with data scientists to build end-to-end machine learning models using Generative AI and LLMs.
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Experience with graph-based data workflows such as Apache Airflow, Meson. Job Summary: We’re looking for a principal ML engineer interested in building optimized, efficient and reliable products, services and interfaces to federate access to data stores, simplify, automate and manage the ML development and deployment ecosystem.
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Highly tuned emotional intelligence, good listener, and deep seated empathy for teams and partnersPrevious experience with machine learning (building models, deploying models, setting up cloud infrastructure and/or data pipelines) and familiarity with major ML frameworks such as XGBoost, PyTorch, AWS SageMaker, etc.
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Requirements Required Skills: AI/ML Mastery: Extensive experience in AI/ML, including deep knowledge of machine learning algorithms, neural networks, and data science methodologies.
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Design and build the data pipelines to train the machine learning algorithms. Job Title: Machine Learning Engineer. Perform analysis on large datasets to discover valuable insights through the use of big data tools.
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machine learning data jobs Title: machine learning in South San Francisco, CA
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