BENGALURU · FULLTIME
ML Engineer-Advanced Analytics
IBM
Bengaluru · onsite · Posted 55d ago
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Undisclosed5–10 yrsfulltimeBengaluru
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Section · 01
About this role
Your Role and Responsibilities:
Your primary responsibilities will include:
As an ML Engineer with Advanced Analytics skills, you will apply your strong understanding of machine learning techniques and their applications to design, develop, and deploy production-ready ML software. You will utilize popular libraries such as scikit-learn, TensorFlow, or PyTorch to ensure that ML solutions are efficient, scalable, and maintainable.
Your primary responsibilities will include:
Design and Develop ML Software: Apply various ML algorithms, including regression, classification, clustering, and recommender systems, to create production-ready ML software.
Deploy and Maintain ML Solutions: Ensure that ML solutions are efficient, scalable, and maintainable, and deploy them to meet business needs.
Apply ML Techniques: Utilize machine learning techniques to solve complex problems and improve system performance.
Develop Distributed Systems: Design and develop distributed systems and ML components to support large-scale ML applications.
Implement ML Algorithms: Implement ML algorithms using popular libraries such as scikit-learn, TensorFlow, or PyTorch to drive business outcomes.
Required Education:
Bachelor's Degree
Preferred education
Master's Degree
Required Technical and Professional Expertise:
Machine Learning Techniques: Exposure to applying various ML algorithms, including regression, classification, clustering, and recommender systems, to solve complex problems and improve system performance.
ML Software Development: Experience working with popular libraries such as scikit-learn, TensorFlow, or PyTorch to design, develop, and deploy production-ready ML software.
Distributed Systems: Exposure to designing and developing distributed systems and ML components to support large-scale ML applications.
ML Solution Deployment: Experience working with deploying and maintaining ML solutions to ensure they are efficient, scalable, and maintainable.
Algorithm Implementation: Exposure to implementing ML algorithms using popular libraries to drive business outcomes.
Preferred Technical and Professional Experience:
Popular Library Proficiency: Exposure to utilizing popular libraries such as scikit-learn, TensorFlow, or PyTorch for designing, developing, and deploying production-ready ML software.
Distributed System Knowledge: Exposure to designing and developing distributed systems and ML components to support large-scale ML applications.
ML Algorithm Implementation: Exposure to implementing ML algorithms using popular libraries to drive business outcomes.
Years of Experience:
5 - 10
5 - 10
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Section · 02
Skills
MatlabAimlCreocSimulinkamazon web servicesNatural Language ProcessingrEmbedded CcanoeAnalyticsC plus plusWiring Harness DesignPythonSQLJavaDeep LearningData ScienceArtificial IntelligenceMachine LearningDesign Engineering
Section · Company
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