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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing, developing, and maintaining scalable AI/ML systems, with a strong focus on MLOps and cloud technologies, particularly within the Azure ecosystem. Proficient in leveraging Python and related ML libraries to deliver end-to-end solutions while ensuring quality and efficiency in AI/ML pipelines.
Highest-signal resume keywords
AI/ML System DesignMLOps / LLMOps / AgentOpsPython ProgrammingAzure Cloud TechnologiesDatabricks
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI/ML LifecycleMLflowREST API for ML Model ServingDockerRelational DatabasesNon-Relational DatabasesSoftware Engineering Best PracticesAgile MethodologiesModel MonitoringBatch and Real-Time Pipelines
Soft Skills
Cross-Functional Collaboration
Tools & Technologies
Azure FoundryAzure BicepAzure MLAzure Cloud StorageLangChainVectorDBsEvaluation Frameworks
Industry Keywords
Open-Source ContributionAI/ML Products and Services
Tech Stack
Tools & technologiesAzureCloudDockerPython
About the role
Key responsibilities & impact- 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
What you’ll need- 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)
- Contribution to open-source libraries is a plus
Benefits
Comp & perks- 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
- Remote work from abroad policy
- Meals and Transportation Vouchers (Coverflex card)
- Dental Benefits
- Life & Accident Insurance + Private Health Insurance
- Paid employee volunteer day
- Paid moving day (1/year)
- Time off: 1 Community Service Day + 1 Personal Day
- Summer Hours in July and August (36 hours per week)
- Hybrid Monthly Allowance for electricity and Internet