AI/ML Platform Developer

4 days ago

Mandaluyong City, National Capital Region, Philippines beBeeArtificialintelligence Full time ₱1,000,000 - ₱1,200,000

AI/ML Platform Engineer

We are seeking a hands-on engineer to help build our AI/ML platform from the ground up. You 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.

This is a greenfield build, combining MLOps and Machine Learning engineering responsibilities into a single, integrated position. 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. As the platform grows, you will help shape best practices and define clear processes, ensuring responsibilities remain focused and sustainable.

Responsibilities:

  • Collaborate with the team to implement the initial AI/ML architecture on Azure Databricks, setting up infrastructure and workflows.
  • Design and build scalable, reproducible ML pipelines for data ingestion, feature engineering, training, testing, and deployment.
  • Ensure version control and collaboration through Git-based workflows.
  • Establish processes for automated model training, tuning, deployment, and monitoring using Databricks MLflow and Azure ML Pipelines.
  • Define and manage model registries, versioning, and traceability.
  • Implement strict controls for data access, lineage, and security.
  • Ensure all pipelines and models comply with regulatory requirements, auditability, and ML ethics standards.
  • 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.
  • Integrate pipelines with Azure DevOps or GitHub Actions for automated testing, validation, and deployment.
  • Support infrastructure-as-code with Terraform, Bicep, or ARM templates to ensure reproducibility and scalability.
  • Partner with data scientists to productionize research prototypes.
  • Document workflows, governance processes, and best practices for ongoing maintainability.

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.
  • Azure certifications (e.g., Azure Data Scientist Associate, Azure Solutions Architect, or Azure DevOps Engineer).

Soft Skills:

  • Curiosity and eagerness to learn.
  • Collaborative mindset.
  • Adaptability.
  • Problem-solving skills.
  • Attention to detail.
  • Proactive communication.

How Can You Contribute?

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