Artificial Intelligence Engineer

1 day ago

Mandaluyong City, National Capital Region, Philippines beBeeMachine Full time $90,000 - $110,000
AI/ML Platform Development Specialist

We are seeking an experienced professional to lead the development of our AI/ML platform from the ground up.

The successful candidate will work collaboratively with a cross-functional team to implement a predefined architecture and establish the foundations of a production-grade system that adheres to strict data governance and compliance standards.

  • Design and build scalable, reproducible ML pipelines for data ingestion, feature engineering, training, testing, and deployment.
  • Establish processes for automated model training, tuning, deployment, and monitoring using Databricks MLflow and Azure ML Pipelines.

As the platform grows, you will help shape best practices and define clear processes, ensuring responsibilities remain focused and sustainable.

Key Responsibilities:

Platform Development
  • Implement the initial AI/ML architecture on Azure Databricks, setting up infrastructure and workflows.
  • Ensure version control and collaboration through Git-based workflows.
Data Governance & Compliance
  • Implement strict controls for data access, lineage, and security.
  • Ensure all pipelines and models comply with regulatory requirements, auditability, and ML ethics standards.
Deployment & Monitoring
  • Deploy models for real-time and batch inference using MLflow.
  • Contribute to monitoring frameworks for drift detection, latency, and performance degradation using Azure Monitor or equivalent.

You will contribute across the end-to-end ML lifecycle from data pipelines and governance through to model deployment and monitoring with a strong focus on collaboration.

Skill Requirements:

  • Strong proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow.
  • Hands-on experience with Git for pipeline development (branching strategies, code reviews, version control best practices).

Preferred Qualifications:

  • Familiarity with Generative AI, LLM deployment, or RAG pipelines using Azure OpenAI Service, LangChain, or open-source LLMs.
  • Experience with vector databases (e.g., FAISS, Milvus, Pinecone) and model explainability tools.

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