Machine Learning Engineer

Introduction

In this role, you’ll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.

A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.

You’ll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.

Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you’ll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.

Your Role and Responsibilities

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs.

Your Primary Responsibilities Include

• Strategic Data Model Design and ETL Optimization: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements.
• Robust Data Infrastructure Management: Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization.
• Seamless Data Accessibility and Security Coordination: Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too.
  
  

Required Technical and Professional Expertise

• Experience in data science, AI, and ML, with a focus on AI
• Knowledge of libraries like Pytorch or similar,
• Proficient in Python
  
  

Preferred Technical And Professional Expertise

Nice to have:

• Understanding of MLOps and DevOps practices and tools
• Strong understanding of AI governance frameworks and regulations & data governance and ethics