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Capgemini
Required Qualifications
· Any B. Tech or M. Tech, bachelor’s or master’s degree, Data Science, Statistics, or a related field
· 6–9 years of experience building and maintaining production-grade AI solutions.
· Proven experience working in enterprise-scale environments delivering end-to-end AI systems.
· Optional - Strong proficiency in Databricks, Azure Stack, and core Azure services.
· In-depth knowledge of machine learning algorithms and model evaluation techniques.
· Hands-on programming experience with Python.
· Familiarity with generative AI technologies such as GANs and their applications.
· Strong understanding of cloud-based and distributed system architectures.
· Excellent communication skills to collaborate with technical and non-technical stakeholders.
· Strong analytical and problem-solving abilities with a passion for innovation.
Preferred Skills
· Experience with Azure OpenAI and large language model–based solutions.
· Hands-on experience with MLOps tools such as MLflow and CI/CD pipelines for ML.
· Knowledge of containerized AI workloads using Docker and Kubernetes.
· Understanding of Responsible AI, data privacy, and ethical AI practices.
· Experience mentoring engineers or providing technical leadership.
Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.1. Applies scientific methods to analyse and solve software engineering problems.2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders.KPMG
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