.Cegid is a European leader in cloud business management solutions for finance (cash-flow, tax, ERP), human resources (payroll, talent management), CPAs, retail and entrepreneurial sectors.
In today's rapidly changing world, Cegid & its 5,000 employees make more possible by helping their 750,000 customers unleash their potential thanks to innovative and purposeful business solutions.Make more possible, is our vocation.
It reflects who we are, how and why we do things the way we do them for our clients.
Thanks to this, we can affirm that we work every day to shape your future, ours and our clients' industries' future.
A future we have been defining for years with our employees, by inventing solutions that change the way people work, for a sustainable performance.
@AI FactoryThe AI Factory is dedicated to advancing our management software through AI innovation.
Our primary goal is to seamlessly integrate AI features into our product line, either by enhancing functionality and user experience or by recreating user workflows to take full advantage of AI technology.What will you achieve?CEGID is seeking a Senior Machine Learning Engineer to join our Artificial Intelligence Center of Expertise (CoE).
In this role, you will be responsible for embedding Artificial Intelligence into CEGID's management software products portfolio.
Specifically, this role will be responsible for defining ML best practices, building and deploying ML models pipelines for a range of our products.As a Senior Machine Learning Engineer, you will:Build and maintain machine learning pipelines to deploy and maintain models in production; Implement MLOps andLLMOps concepts to streamline the machine learning lifecycle; Develop and maintain scalable, robust, and efficient machine learning infrastructure; Collaborate with data science teams to understand model requirements and ensure successful integration into software products; Communicate with different stakeholders such as data scientists, software engineers and cloud architects to ensure models are deployed and monitored in production environments according to best practices; Troubleshoot and resolve technical issues related to machine learning models and infrastructure; Stay up-to-date with the latest developments in machine learning and artificial intelligence