APPLICATION DEVELOPER

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 47,000 world-class talents, Eviden expands the possibilities of data and technology, now and for generations to come.

Position- MLOps engineer
Location- Remote (USA)
Duration- Fulltime

Salary: $100K-$115K FTE benefits

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). Feature Store Management: * 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. * Collaborate with data engineers and data scientists to ensure the integrity and efficiency of data used in 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. Continuous Monitoring and Optimization: * Monitor ML systems in production, identify improvement opportunities, and implement optimizations. * Participate in support rotations and participate in support calls as necessary.

Let's grow together.