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AWS Graviton powered instances provide the best price performance and support a wide range of computing workloads including application servers, microservices, high-performance computing (HPC), CPU-based machine learning (ML) inference, video encoding, electronic design automation, gaming, open-source databases, and in-memory caches.
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Production Runtime Experience (PRX) is a Technology Business Unit focused on running scalable production management services with a mandate of operational excellence and operational risk reduction that is achieved through large scale automation, best-in-class engineering and by leveraging data sciences and machine learning.
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Powered by NEO, One Network’s machine learning and intelligent agent technology, it enables seamless planning and execution, across inbound supply, outbound order fulfillment, and logistics, matching demand with available supply in real-time.
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Independently design and evaluate predictive models and advanced algorithms for decision-making processes using statistical modeling and machine learning techniques. or similar; full software development lifecycle, including requirements gathering, design, coding, testing, documentation, deployment, and production support; microservices architecture, REST APIs, and data analysis on large datasets using SQL, Python, or PySpark; and Sybase and other relational database management systems (RDBMS) as well as database query language.
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We are hiring a Principal Data Scientist with deep expertise in machine learning and AI and experience in developing production quality solutions which deliver a huge business impact.
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Proficiency in machine learning, deep learning, and data mining techniques. The ideal candidate should have at least 5 years of professional experience as a Machine Learning Developer and at least 1-2 years of expertise in implementing Gen AI technologies to derive meaningful insights from large datasets.
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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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The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production AI systems.
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Depth of knowledge machine learning techniques involving natural language processing and recommender systems. Practical experience designing, building and deploying machine learning models.
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Experience with Artificial Intelligence and Machine Learning applications in a manufacturing environment. Employee will be required to wear all plant-mandatory PPE when on production floor, including hard hat, safety glasses, steel toe boots, ear protection, and face covering as per CDC and State guidelines.
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You will use quality metrics to select machine learning models that will be deployed in the production environment. You have experience with statistical modeling, hypothesis testing, machine learning, deep learning, optimization and other data science techniques to implement end-to-end data science projects.
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Our data and storage solutions empower machine learning, artificial intelligence, cloud-based technologies, and other modern tools to create differential and scalable products. Participating in an on-call rotation and collaborating with other teams, such as SRE, to solve production issues.
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Knowledge or expertise in one or more of the following is a plus: visual design, machine learning, mobile applications, web applications, messaging interfaces, illustration, video/film production.
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Machine Learning Engineer that work with Data Scientists in a SDLC environment into production. The main function of a machine learning engineer is to design, develop, implement, test, and maintain multi-platform machine learning software systems.
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Lead the deployment of both generative and traditional machine learning models into production, ensuring scalability and reliability. Strong proficiency in machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn, with a specialization in generative modeling libraries.
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production machine learning jobs in Dallas, CO, Germany
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