About EcoVadis
EcoVadis is the leading provider of business sustainability ratings. Our solutions are backed by an international team of experts and powerful technology. We analyze data and build sustainability scorecards that give companies actionable insights into their environmental, social and ethical risks. We are looking for a highly motivated Senior AI/ML Engineer to join our growing AI Center of Excellence, responsible for using AI and machine learning to drive innovation across the organization.
Responsibilities
•Leverage data to solve business problems of various business units at EcoVadis
•Design, develop, deploy and maintain scalable AI/ML systems
•Design AI/ML pipelines by applying the best practices in MLOps / LLMOps / AgentOps
•Build AI/ML engineering infrastructure and systems to orchestrate batch and real-time pipelines
•Run large-scale experiments and tests to ensure quality and efficiency of ML and data pipelines
•Partner with scientists and engineers to make AI/ML models accessible to end-users and downstream processes
•Leverage Python, MLflow, Azure stack (e.g., Azure cloud, Azure ML, Azure Foundry) and Databricks to deliver end-to-end solutions
Requirements
•Outgoing personality along with an exceptional level of drive and a desire to pursue a career in an international and dynamic environment
•Excellent verbal and written communication, critical thinking and analytical skills
•Degree in Computer Science, Mathematics, Engineering, or a related technical discipline
•Industry experience in driving, designing and implementing production-grade AI/ML systems and integrating those into business applications as well as model monitoring at scale
•Strong programming skills in Python and related ML libraries
•Strong experience of AI/ML lifecycle, principles, and MLOps / LLMOps / AgentOps tooling (e.g., MLflow, LangChain, VectorDBs, Evaluation frameworks, etc.)
•Experience in cloud technology, preferably Azure and its ecosystem (e.g., Azure Foundry, Azure Bicep, AzureML and Azure Cloud Storage) and Databricks
•Solid understanding of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
•Experience with REST API for ML model serving
•Experience with Docker and container orchestration
•Experience with relational and non-relational databases
•Experience in cross-functional collaboration in the development of AI/ML products and services (e.g., Engineers, Product Managers)
Nice to have
•Contribution to open-source libraries
Benefits
•Support with all the necessary office and IT equipment
•Flexible working hours
•Wellness allowance for mental and physical wellbeing
•Access to professional mental health support
•Referral bonus policy
•Learning and development
•Sustainability events and community involvement
•Peer recognition program
•Employee-led resource groups
•Optional (fully covered or co-financed) health care and life insurance
•Multisport card
•Multikafeteria
•Lunch card
•Hybrid work organization
•Remote work from abroad policy
•Internet and electricity bill allowance
•Additional day for community service when volunteering
