Join Capgemini as an LLMOps Engineer and contribute to transforming leading organizations through technology. This role is perfect for experienced professionals seeking to shape their careers within a collaborative global community. You'll help unlock the value of technology, building a more sustainable and inclusive world.

Capgemini is a global leader in business and technology transformation, powered by AI. With a rich heritage and a presence in over 50 countries, we deliver end-to-end solutions leveraging deep industry expertise and a strong partner ecosystem.

Design, implement, and maintain robust ML pipelines for model training, evaluation, and deployment. Collaborate with data scientists and software engineers to operationalize ML models using serving frameworks like TensorFlow Serving and TorchServe. Develop and maintain CI/CD pipelines specifically for ML workflows, ensuring efficient and repeatable processes.

Implement comprehensive monitoring and logging solutions for ML models. Optimize ML infrastructure to enhance performance, ensure scalability, and manage costs effectively. Provide GenAI scalability and integration, including ops support for Large Language Models and incident management.

You will be instrumental in providing ops support for Large Language Models, managing incidents, and offering user support. Responsibilities include monitoring and maintaining GenAI solutions, focusing on performance, user interaction, and efficacy. You'll conduct guardrail reviews, including bias audits and other checks relevant to implemented GenAI solutions.

This role also involves supporting code management with proactive code optimization. You will implement cost and performance optimizations for Gen AI applications, informed by LLMOps monitoring data. An appreciation for hybrid work arrangements and a commitment to career growth and professional development are key.