Eviden, part of the Atos Group, with an annual revenue of circa € 5 billion is a global leader in data-driven, trusted and sustainable digital transformation. As a next generation digital business with worldwide leading positions in digital, cloud, data, advanced computing and security, it brings deep expertise for all industries in more than 47 countries. By uniting unique high-end technologies across the full digital continuum with 53,000 world-class talents, Eviden expands the possibilities of data and technology, now and for generations to come.

Position- MLOps Engineer

Location- Remote (US)

Duration- Fulltime

Job description :

We are seeking a dynamic Senior Software Engineer with an ML focus to lead the integration and operationalization of machine learning models in our Search area. This role requires collaboration with data scientists and leadership teams, and a strong foundation in MLOps methodologies. Experience in diverse ML platforms, including Google Vertex AI and other cloud and open-source technologies, is essential. The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of our ML infrastructure. Hands-on experience working on recommender systems, drawing from ML techniques such as embedding based retrieval, reinforcement learning, and transformers. • Software engineering skills to work with teams integrating the recommender systems into customer facing products. • Experience in AB testing and iterative optimization using data driven approaches. • Understanding of infrastructure needs required to deploy ML systems (CPU/GPU, networking infrastructure). • Efficiently manage, share, and reuse machine learning features at scale using Vertex AI Feature Store. • Implement feature stores as a central repository for maintaining transparency in ML operations across the organization. • Enable feature delivery with endpoint exposure while maintaining authority and security features. Data Management and Collaboration: • Assist as needed with data labeling and management, ensuring high-quality data for ML models. • Ensure end-to-end integration for data to AI, including the use of BigTable / BigQuery for executing machine learning models on business intelligence tools.