AI Engineer
Makati City, Metro ManilaPosted 11 days agoJobStreet
Skills mentioned
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About the role
Avensys is a reputed global IT professional services company headquartered in Singapore. Our service spectrum includes enterprise solution consulting, business intelligence, business process automation and managed services. Given our decade of success, we have evolved to become one of the top trusted providers in Singapore and service a client base across banking and financial services, insurance, information technology, healthcare, retail and supply chain. We are currently looking for AI Engineer who has proven track record in IT Industry. This is an exciting opportunity to expand your skill set, achieve job satisfaction and work-life balance. More details as below. Role: AI Engineer
- Employment Type: Permanent Role
- Notice Period: Immediate Joiners/ 1 months
- Work Mode: Hybrid (2 days work from office)
Work Location: Makati City, Philippines Mandatory skills: AI & Machine Learning Engineering, Cloud AI & Data Platforms, Data Engineering & Integration, MLOps & Deployment. Job Summary: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, Auto
- ML, 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 & DeploymentCI/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
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).
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