Ml Engineer Jobs

About The Position

Requirements

• Degree in Computer Science, Mathematics, Engineering, or a related technical discipline.
• Industry experience driving, designing, and implementing production-grade AI/ML systems, integrating them into business applications, and monitoring models at scale.
• Strong programming skills in Python and related ML libraries.
• Strong experience with the AI/ML lifecycle, its principles, and MLOps, LLMOps, or AgentOps tooling.
• Experience with cloud technology and Databricks; Azure experience is preferred.
• 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 APIs for ML model serving.
• Experience with Docker and container orchestration.
• Experience with relational and non-relational databases.
• Experience collaborating cross-functionally on AI/ML products and services, for example with engineers and product managers.
• Outgoing personality, drive, and interest in an international and dynamic work environment.
• Excellent verbal and written communication, critical-thinking, and analytical skills.

Nice To Haves

• Experience with Azure ecosystem tools such as Azure Foundry, Azure Bicep, Azure ML, and Azure Cloud Storage.
• Familiarity with tools such as MLflow, LangChain, vector databases, and evaluation frameworks.
• Contributions to open-source libraries.

Responsibilities

• Use data to solve business problems for various EcoVadis business units.
• Design, develop, deploy, and maintain scalable AI/ML systems.
• Design AI/ML pipelines using MLOps, LLMOps, and AgentOps best practices.
• Build AI/ML engineering infrastructure and systems to orchestrate batch and real-time pipelines.
• Run large-scale experiments and tests to ensure the 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.
• Deliver end-to-end solutions using Python, MLflow, the Azure ecosystem, and Databricks.

Benefits

• Support with 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
• Remote work from abroad policy
• Meals and transportation vouchers (Coverflex card)
• Dental benefits
• Life and accident insurance
• Private health insurance
• Paid employee volunteer day
• Paid moving day (one per year)
• One Community Service Day and one Personal Day
• Summer hours in July and August (36 hours per week)
• Hybrid monthly allowance for electricity and internet