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.
Within Capgemini Engineering, Hybrid Intelligence is our international team of data and artificial intelligence experts. Our work is a unique blend of applied mathematics, scientific computing, artificial intelligence, and software engineering. We deliver groundbreaking, multidisciplinary solutions to our clients, driven by research and innovation. Our mission is to tackle humanity’s generational challenges—from discovering new medical treatments to harnessing green energy. We are committed to fostering a diverse and inclusive environment and are proud to be an equal opportunity employer. We value people for who they are and embrace the diversity they bring to our team.
Key Responsibilities
Design and execute test plans for AI solutions, including acceptance testing, regression testing, and functional validation.
Ensure that models meet the defined requirements based on the SRS.
Assess the quality and balance of datasets using test split techniques and cross-validation.
Generate synthetic data to resolve imbalanced dataset problems.
Automate test processes using frameworks such as Pytest.
Collaborate closely with development and data science teams using Agile methodologies and pair programming.
Document testing processes and produce quality assurance reports for models and data.
Must-Have:
Proven experience in software testing, particularly within AI-driven projects.
Strong understanding of dataset validation and machine learning model evaluation.
Proficiency in Python for data science (including libraries such as Pandas, NumPy, Scikit-learn).
Hands-on experience with testing tools and methodologies (e.g., Pytest, TDD, Agile).
Knowledge of feature engineering and data preprocessing techniques.
Nice-to-Have:
Familiarity with other programming languages like Java, C#, or R.
Experience with big data technologies and advanced data mining techniques.
Background in building custom datasets and using synthetic data generation tools.
Why You'll Love Working Here
We offer a comprehensive set of development and work-life balance benefits, including (but not limited to):
Buddy Program to support you during your first steps with us.
Generous time off: 24 vacation days + 2 personal days + December 24th and 31st off. You also have the option to purchase up to 7 additional vacation days per year.
Continuous learning opportunities through MyLearning, Capgemini University, and our Digital Campuses. You'll have access to platforms such as Coursera, Udemy, Pluralsight, Harvard Manager Mentor, and Education First for language learning (English, French, German, etc.).
A global DATA & AI community, where you can collaborate with experts from around the world.
#J-18808-Ljbffr