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Senior Associate L2 - DS-AI & Machine Learning
Senior Associate L2 - DS-AI & Machine Learning-January 2024
Bangalore
Jan 19, 2025
ABOUT PUBLICIS SAPIENT
Publicis Sapient uses strategy, consulting, experience, engineering, and a culture of problem-solving creativity, to help our clients thrive.
10,000+ employees
Consulting, Technology
VIEW COMPANY PROFILE >>
About Senior Associate L2 - DS-AI & Machine Learning

  Description

  Publicis Sapient is looking for a highly capable Machine Learning Engineer to join its Data CoE. As part of the team, you will be responsible for creating data-driven solutions. You will be working on various MLOps stages namely deployment, governance, reproducibility, and monitoring of ML models. You will be evaluating new or existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities. You will be participating in the development of machine learning apps that meet business needs. You will also communicate with clients and stakeholders to understand business objectives and how to achieve them using machine learning.

  Your Impact:

  Consulting with clients and stakeholders to determine and refine machine learning objectives.Building and deploying machine learning systems and taking care of delivering ML models to end users.Developing a scalable system known as a machine learning pipeline to automate and manage ML processes.Support model implementation and execution within a targeted environment.Designing machine learning systems and artificial intelligence (AI) software to automate predictive models and make those model work in production environmentTransforming data science prototypes and applying appropriate MLOps framework and tools.Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.

  Qualifications

  Gender-Neutral Policy18 paid holidays throughout the year.Generous parental leave and new parent transition programFlexible work arrangementsEmployee Assistance Programs to help you in wellness and well being

  Additional Information

  Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients' businesses through designing the products and services their customers truly valu

  Company Description

  Publicis Sapient is looking for a highly capable Machine Learning Engineer to join its Data CoE. As part of the team, you will be responsible for creating data-driven solutions. You will be working on various MLOps stages namely deployment, governance, reproducibility, and monitoring of ML models. You will be evaluating new or existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities. You will be participating in the development of machine learning apps that meet business needs. You will also communicate with clients and stakeholders to understand business objectives and how to achieve them using machine learning.

  Your Impact:

  Consulting with clients and stakeholders to determine and refine machine learning objectives.Building and deploying machine learning systems and taking care of delivering ML models to end users.Developing a scalable system known as a machine learning pipeline to automate and manage ML processes.Support model implementation and execution within a targeted environment.Designing machine learning systems and artificial intelligence (AI) software to automate predictive models and make those model work in production environmentTransforming data science prototypes and applying appropriate MLOps framework and tools.Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.

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