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Machine Learning Engineer (MLOps)

Tecnología
Capgemini Engineering
Hace 3 semanasHasta 6/6/2026
Tiempo completo100% Remoto

Descripción del puesto

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities.

Where you can make a difference. Where no two days are the same

Your role:

We are looking for a highly capable Senior MLOps Engineer with a strong Software Engineering and DevOps background. As a Senior MLOps Engineer, you will be embedded and supporting a revenue generation or cost optimization project, ensuring its success in production by improving the code, creating automated CI/CD testing, and developing frameworks that can be reused for other similar projects.
  • Build, maintain, and document machine learning frameworks (python packages) used across multiple projects.
  • Support a project team with Data Scientists, Business Stakeholders, Analysts, and Data Engineers.
  • Develop reusable feature stores for rules-based and AI/ML models.
  • Implement monitoring capabilities for model performance and effectiveness in production.
  • Automate CI/CD testing and deployments incorporating MLOps best practices.

Required:

  • Bachelor's degree in software engineering, computer science, data science, mathematics, or a related field.
  • 5+ years of overall experience in Data Analytics.
  • Sharp critical thinking skills and ability to learn and question complex processes and solutions.
  • Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
  • Experience creating python packages
  • Well-developed software engineering skills, including use of proper development, QA, and production environments, object-oriented programming, version control, and knowledge of multiple programming languages.
  • Proficiency in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
  • Proficiency in SQL.

Preferred Requirements:

  • Master’s or PhD degree in computer science, data science, mathematics, or a related field.
  • Experience with sensor data or other noisy data types.
  • Experience with Agile Software Development.
  • Experience in a large corporation or consulting firm with focus in marketing strategies, modeling, CRM and management sciences/statistics highly desired.
  • Familiarity with frameworks and languages designed for big-data analytics, including Spark and Azure Data Factory.
  • Experience with MLOps and ML experiment tracking tools, such as Azure DevOps and MLFlow or similar.
  • Experience with cloud computing services such as Microsoft Azure, Amazon Web Services and/or Google Cloud Platform.
  • Familiarity with different data science techniques: statistics, machine learning, or cognitive AI.

What We Offer

  • Stable Employment: Permanent contract offering long-term job security.
  • Learning & Development: Access to a wide range of online training platforms and professional development resources.
  • Language Training: Weekly virtual English classes and conversation sessions with certified instructors.

Online

Courses for different languages.
  • Health Coverage: Comprehensive prepaid medical and dental plans.
  • Insurance Protection: Life and accident insurance for peace of mind.
  • Wellness Perks: Discounts and benefits through fitness and technology partnerships.
  • Special Occasion benefits.

About Capgemini

At Capgemini Colombia, 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.
Keywords
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