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Position SummaryAs a Sr Machine Learning Engineer for Analytics and Behavioral Change team, you will be working on billions of records of retail and healthcare data. Exposure/understanding DevOps best practice and CI/CD EducationBachelor’s Degree in Computer Science, Engineering, Machine Learning, or related field or equivalent experience.
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Interest in Data Integrations, machine learning, and autonomic systemsInterest in Cloud architecture with Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Additional Qualifications Expertise with Golang, Rust, Java or similar OO languages for server side developmentExperience with Containers and KubernetesExperience with distributed systemsAppreciation for elegant design and well-crafted codeSubscribe to agile software development principlesPassion for collaboration and sharing ideasCreate new approaches to innovate our architecture Nice to Have: Interest in learning new technologies and getting outside comfort zone.
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Strong background in implementing signal processing or machine learning algorithms in C. Design and develop time-critical signal processing and machine learning algorithms to process information from physiological signals acquired from wearable sensors.
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Applying next-gen technology, high-density storage and machine learning to solve today's complex distribution challenges, Symbotic enables companies to move goods with unmatched speed, agility, accuracy and efficiency.
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Who We are Looking For: The Machine Learning Engineer sits inside of a new start-up within our larger corporation and will be responsible for proposing, planning, executing, and analyzing research and development machine learning projects related to the field of advanced manufacturing artificial intelligence.
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The initial work focuses on the development of an ultra-low latency audio router to enable rapid prototyping of next generation noise processing and machine learning algorithms. The tool infrastructure engineering team is looking for an advanced development (A/D) electrical mixed-signal engineer with a strong interest in working on audio architectures and systems.
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Demonstrated expertise programming in MATLAB and Simulink; and implementing the data science workflow, including applying statistical techniques and machine learning algorithms to support data model architecture.
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Knowledge in application of Machine Learning and Artificial Intelligence methodologies. Process engineer with a PhD in process modeling and 10 years industrial / academic experience, or MSc with 15 years’ experience.
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Familiarity of AI Technologies e.g., Generative/Cognitive AI framework/models, Machine Learning/Deep Learning, AI platforms/libraries (e.g., Hugging Face, TensorFlow) and Open-Source Machine Learning framework (PyTorch.
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Growth Potential: Developing a strong foundation in data analytics paves the way for career growth into advanced roles such as data scientist, machine learning engineer, or data engineer.
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The Machine Learning Engineer is responsible for proposing, planning, executing, and analyzing research and development machine learning projects related to the field of advanced manufacturing artificial intelligence.
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Basic knowledge of image processing, analysis, and deep learning techniques. Technical Support supports Cognex customers using our sophisticated, industry-leading machine vision software in their cutting edge factory automation applications to analyze imagery (intensity, color, density, Z-data, etc.
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You will be part of TITAN team and partner with both business and technology teams to design and develop in-house data driven solutions for complex decision-making problems through systematic application of computer science, analytics, mathematical optimization, and machine learning as well as applying cutting edge technologies in the areas of Inventory Management, Order Lifecycle (capture, management, and fulfillment), and Supply Chain.
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Engineers in this group typically have experience with deep learning, image analysis, machine vision, statistical learning, or signal processing. As a Scientist on this team, you will be responsible for researching, designing, implementing and deploying state-of-the-art deep learning algorithms for industrial machine vision applications, with a mission to innovate on behalf of customers and make this technology accessible to a broad range of users and platforms.
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