Senior Machine Learning Engineer - Mandaluyong - Maya

    Maya
    Maya Mandaluyong

    4 araw ang nakalipas

    ₱1,500,000 - ₱2,800,000 (PHP) bawat taon *
    Paglalarawan

    Maya continues to build the future of FinTech in the Philippines—and Enterprise AI sits at the center of that transformation. We're looking for a Senior Machine Learning Engineer for Enterprise AI who will join as a pioneer member of the Enterprise AI team. This role will establish our ML engineering practice and build production‑ready AI models that power automation and smarter decision‑making across Maya.

    If you're passionate about LLMs, model lifecycle management, and building secure, compliant, production‑grade AI systems—this is your team.

    What You'll Do

    Build Enterprise‑Grade ML Models

    • Design and develop custom ML models for internal use cases (document classification, entity extraction, fraud pattern detection, process automation).
    • Fine‑tune foundation models (LLMs, vision models) on Maya‑specific datasets.

    Own the ML Lifecycle

    • Build training datasets (with privacy compliance).
    • Set baseline performance metrics and continuously monitor production models.
    • Implement automated evaluation pipelines to detect drift and data quality issues.
    • Create dashboards and alerts for accuracy, latency, error rates, and business KPIs.

    Engineer for Production

    • Deploy models to containerized environments supported by Maya.
    • Build scalable data pipelines for training, evaluation, and inference using Python + SQL.
    • Integrate models into automation workflows (e.g., n8n via REST APIs).

    Governance, Compliance & Documentation

    • Ensure all models comply with BSP and regulatory requirements.
    • Maintain audit trails, explainability, and secure access to sensitive datasets.
    • Document model architecture, training procedures, and deployment guides.

    Collaboration & Enablement

    • Partner closely with orchestration engineers, business teams, and other specialists.
    • Conduct knowledge‑transfer sessions to upskill internal teams on ML best practices.

    What You Bring

    Technical Expertise

    • 5+ years building and deploying ML models using TensorFlow, PyTorch, scikit‑learn.
    • Strong experience fine‑tuning foundation models (LLMs, CV models).
    • Solid NLP and/or CV experience—especially for document understanding.
    • Understanding of interpretability, explainability, and regulated ML requirements.

    Data Engineering & MLOps

    • Strong Python and SQL skills.
    • 3+ years working with cloud platforms (AWS preferred; Azure acceptable).
    • Experience with containerization, experiment tracking, model registries, and CI/CD.
    • Ability to monitor production systems and build observability tools.

    Integration & Systems Thinking

    • Experience integrating ML models with automation tools (e.g., n8n) and enterprise systems (Salesforce, SAP, MS platforms).
    • Knowledge of REST APIs and secure authentication.

    Domain Advantage

    • Experience in regulated industries (banking, finance, healthcare) is a strong plus.
    • Familiarity with financial or government documents, IDP, or OCR use cases is highly desirable.

    Behavioral & Soft Skills

    • Strong analytical mindset and problem‑solving ability.
    • Excellent communication skills for technical and non‑technical audiences.
    • Self‑starter who can own end‑to‑end ML projects.
    • Detail‑oriented, highly compliant, and security‑conscious.

    What Success Looks Like

    • Your deployed models consistently hit accuracy, latency (<3s), and precision/recall targets.
    • All production models have active monitoring dashboards and evaluation reports.
    • Model issues are detected quickly with clear runbooks and operational readiness.
    • You establish repeatable model deployment practices for future team members.
    • Regulatory compliance (BSP + internal security guidelines) is always met.
    • You introduce reusable ML frameworks and accelerate AI adoption across Maya.

    Qualifications

    • Bachelor's degree in CS, Data Science, Statistics, Engineering, or equivalent.
    • Master's degree in ML/AI is a plus.
    • AWS ML Specialty or related certifications are a plus.
    • 5+ years ML development experience + 3+ years cloud‑based ML platform experience.
    • Experience with foundation model fine‑tuning and production ML monitoring.

    Ready to build AI that powers the future of finance at Maya?

    If this sounds like you, apply now and help shape the next generation of internal and customer‑facing AI at the #1 FinTech ecosystem in the Philippines.

    * Ang saklaw ng suweldo na ito ay isang pagtatantya na ginawa ng beBee
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