ML Platform Engineer — MLOps & GenAI (Remote)

Lingaro Group Philippines; Manila; Hybrid; PHP 900,000 - 1,500,000; Full time

Benefits offered by this job

Remote work option

Udemy learning platform access

Certificate training programs

Great Place to Work certified

Flexible working hours

Office as an option

Job summary

Lingaro Group Philippines is seeking a data engineer with ML/MLOps focus to implement models into production and manage data pipelines. You will work with Data Science teams to deploy production-ready code, design scalable processing pipelines, and implement ML lifecycle best practices.

Knowledge of GenAI is a plus. Join a diverse team that emphasizes growth, flexibility, and ongoing learning through Udemy courses and internal knowledge sharing.

Qualifications

• Experience building production-ready Python code for microservices/APIs.
• Hands-on ML/AI model development and deployment in production.
• Practical MLOps/LLMOps using AzureML or similar tools.
• Experience with Databricks, Spark/PySpark, and big data pipelines.
• Solid cloud knowledge (Azure or GCP) and CI/CD/DevOps tooling.
• Strong English communication and teamwork skills.

Responsibilities

• Collaborate with Data Science to deploy ML models into production.
• Design, deliver and manage industrialized data processing pipelines.
• Define and implement ML lifecycle and MLOps practices.
• Implement AI/ML/AIOps frameworks and support DS teams.
• Gather knowledge on modern ML architecture and operations.
• Present solutions to clients and document technical details.

Skills

Data engineering

Python programming

MLOps/LLMOps

Databricks

Spark/PySpark

Cloud concepts

CI/CD/DevOps

Teamwork

English fluency

Communication

Tools

AzureML/AzureAI

Databricks

Docker

Kubernetes

GitHub Actions

GitLab

Azure DevOps

Hive

Job description

Lingaro Group Philippines is seeking a data engineer with ML/MLOps focus to implement models into production and manage data pipelines. You will work with Data Science teams to deploy production-ready code, design scalable processing pipelines, and implement ML lifecycle best practices.

Knowledge of GenAI is a plus. Join a diverse team that emphasizes growth, flexibility, and ongoing learning through Udemy courses and internal knowledge sharing.