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Capgemini

Machine Learning Engineer

Posted an hour ago
5-10 years experience
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AI Summary

Build and deploy scalable machine learning solutions and Generative AI applications to drive business outcomes. Collaborate with data engineering and business teams to transition models from experimentation to production environments.

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. 

Your Role

  • Build and deploy machine learning solutions that directly impact business outcomes, including demand forecasting, lead scoring, propensity modeling, and other large-scale predictive analytics use cases.
  • Work extensively with Python, SQL, PySpark, and cloud-based data platforms such as Azure and Databricks to develop scalable ML pipelines and production-grade data workflows.
  • Design, train, optimize, and explain machine learning models using techniques such as XGBoost, LightGBM, and SHAP, ensuring that model outputs are transparent and actionable for business stakeholders.
  • Develop and implement Generative AI solutions, including RAG architectures, vector search, and AI agents with tool usage, while supporting high-volume LLM workloads through APIs and automated processes.
  • Partner closely with Data Engineering, Analytics, and business teams to take models and AI applications from experimentation to production, ensuring reliability, scalability, and measurable business value.
 

Your Profile

  • 5+YOE in machine learning development , including building and deploying production models for forecasting, classification, propensity scoring, lead scoring, or similar business-critical use cases.
  • Advanced Python, SQL, and PySpark skills, with the ability to work on large-scale datasets, optimize data pipelines, and develop end-to-end ML workflows in production environments.
  • Hands-on experience with XGBoost and/or LightGBM in production, including model tuning, evaluation, monitoring, and performance optimization.
  • Proven experience building Generative AI applications, such as RAG systems, vector search solutions, AI agents with tool usage, and large-scale integrations using LLM APIs.
  • Strong cloud and platform expertise, preferably with Azure and Databricks, and experience partnering with Data Engineering and MLOps teams to deploy scalable, production-ready AI solutions.
  • Fluent English level

What you'll love

  • Work on meaningful projects that use technology to solve real-world challenges.
  • Be part of a company that values sustainability, inclusion, and digital equity.
  • Contribute to building a better future for people, planet, and society. 

Need to know

This role can be working from any part of Mexico

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations.

At Capgemini Mexico, we aim to attract the best talent and are committed to creating a diverse and inclusive work environment, so there is no discrimination based on race, sex, sexual orientation, gender identity or expression, or any other characteristic of a person. All applications welcome and will be considered based on merit against the job and/or experience for the position. 

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