ML Engineer-Advanced Analytics

International Business Machines Corporation; Bengaluru; Presencial; INR 1.500.000 - 2.300.000; Jornada completa

Descripción de la vacante

International Business Machines Corporation (IBM) Consulting is seeking an ML Engineer with Advanced Analytics skills to design, develop, and deploy production-ready ML software. You will work with libraries like scikit-learn, TensorFlow, or PyTorch to build scalable ML solutions and distributed components that meet business needs.

Preferred education is a Master’s Degree. You will apply ML techniques to solve complex problems and drive improvements in system performance, with a focus on

Formación

• Experience applying ML algorithms to real problems.
• Experience with scikit-learn, TensorFlow, or PyTorch.
• Experience designing and deploying production ML software.
• Experience designing distributed ML systems.
• Ability to deploy scalable ML solutions.

Responsabilidades

• Design and develop production-ready ML software.
• Deploy ML solutions to meet business needs.
• Apply ML techniques to improve system performance.
• Develop distributed systems and ML components.
• Implement ML algorithms using popular libraries.

Conocimientos

ML Techniques

ML Software Development

Distributed Systems

ML Deployment

Algorithm Implementation

Educación

Master's Degree

Herramientas

scikit-learn

TensorFlow

PyTorch

Descripción del empleo

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

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.

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.