AI/ML Engineer – Business, Data & AI

Experience and Skills

• 6+ years of professional experience in AI/ML Engineering, Data Engineering, Data Science, or a closely related field.
• C1 English level or higher.
• Hands-on experience building or integrating LLM applications, particularly RAG and/or MCP.
• Strong hands-on experience with AWS and cloud-based data architectures
• Experience with traditional machine learning and predictive modeling.
• Advanced SQL skills and experience working with relational databases.
• Experience working with PII, sensitive, or regulated data and implementing appropriate data protection practices.
• Strong understanding of how data is generated, collected, transformed, stored, and consumed within business environments.
• Proven experience designing and implementing end-to-end data pipelines.

• Python
• R
• SQL
• Machine Learning
• Time Series Forecasting
• GCP
• Azure
• AWS
• MLOps
• Statistics
• Data Pipelines

Key Responsibilities

• Business & Data Discovery: Partner with business and technical stakeholders to understand processes, KPIs, data sources, and translate business needs into technical solutions.
• AI & LLM: Build and integrate AI solutions using LLMs, RAG, MCP, and internal enterprise data.
• Machine Learning & Analytics: Develop and support predictive models, forecasting, and other ML use cases as the data platform evolves.
• Data Governance & Communication: Ensure data quality, security, and compliance while communicating insights and technical concepts clearly to non-technical stakeholders.

Nice to Have

• Power BI
• GIS
• Geospatial Analytics
• Survival Analysis
• Customer Segmentation

Benefits