Al/Ml Engineer

OVERVIEW OF WORK

• Design, build, and deploy AI/ML solutions that integrate with enterprise data products, pipelines, and lakehouse architectures.
• Develop and operationalize machine learning models and AI services for use cases such as predictive analytics, anomaly detection, and automation.
• Design and implement Generative AI solutions using LLMs, including RAG architecture and prompt engineering.
• Collaborate with data engineers to embed AI capabilities into data pipelines and ensure seamless integration with data platforms (e.g., Fabric, Databricks).
• Partner with product owners, architects, and stakeholders to translate business needs into AI-driven solutions and reusable components.
• Enable AI readiness across DL&I data products by standardizing model integration, feature engineering, and inference patterns.
• Ensure AI solutions are production-ready by implementing monitoring, logging, and performance optimization practices.
• Support integration of AI outputs into data products, dashboards, and business processes, ensuring interpretability and usability.
• Work with analytics and reporting teams to translate model outputs into business-facing insights and metrics.
• Contribute to enterprise AI governance by ensuring compliance with Responsible AI principles (fairness, transparency, accountability).
• Document AI models, features, pipelines, and assumptions to support reuse, auditability, and knowledge sharing.
• Participate in Agile delivery practices including backlog refinement, sprint planning, and continuous improvement.

TECHNICAL SKILLS

AI & Machine Learning Engineering

• Machine learning model development and lifecycle management
• Feature engineering, model training, evaluation, and deployment
• Familiarity with supervised and unsupervised learning techniques
• Experience with model serving and inference pipelines

Cloud AI & Data Platforms

• Azure AI services (Azure Machine Learning, Cognitive Services, OpenAI integration)
• Microsoft Fabric AI capabilities (Copilot, AutoML, intelligent insights)
• Databricks (MLflow, Model Registry, Delta Lake)
• Understanding of Lakehouse architecture and AI integration patterns

Data Engineering & Integration

• Strong Python and/or SQL for data processing and model integration
• Experience with data pipelines and orchestration tools
• Knowledge of data transformation and feature pipelines
• Integration of AI outputs into downstream analytics systems

MLOps & Deployment

• CI/CD pipelines for machine learning models
• Model versioning, monitoring, and retraining strategies
• Logging, observability, and performance tuning of AI solutions

Delivery & Tooling

• Azure DevOps (ADO) for backlog and work tracking
• Git-based source control for code and model artifacts
• Experience with collaborative development workflows

SOFT SKILLS:

• Strong problem-solving and analytical thinking, with a structured and detail-oriented approach
• Ability to translate complex technical concepts into business-relevant insights
• Effective communication across technical and non-technical stakeholders
• Strong collaboration skills across product, engineering, and architecture teams
• Influencing skills to promote AI adoption and data-driven practices
• Strong documentation and knowledge-sharing discipline
• Continuous learning mindset, especially in rapidly evolving AI technologies
• Comfortable working in Agile, fast-paced delivery environments

DOMAIN KNOWLEDGE:

• Understanding of enterprise data platforms and lakehouse architectures
• Familiarity with IT operational data and enterprise analytics use cases
• Experience with ServiceNow, its architecture, and data
• Awareness of data governance, data quality, and compliance considerations
• Experience with integrating AI solutions into enterprise workflows and systems
• Understanding of Responsible AI principles including fairness, transparency, bias mitigation, and auditability
• Exposure to enterprise-scale data environments and performance considerations

DETAILS:

• Dayshift
• Hybrid setup in Makati Ayala
• Full-time