MLOps Developer/Engineer

2 days ago

Ortigas Metro Manila, Philippines Seven Seven Global Services, Inc. Full time ₱900,000 - ₱1,200,000 per year

About the Role

We are looking for an MLOps Engineer/Developer to design, build, and maintain machine learning pipelines and resilient data systems. You will work hands-on in developing and deploying ML models, automating workflows, and enhancing data platforms, while also contributing to migration projects and proof-of-concepts (POCs).

Key Responsibilities

  • Develop and maintain end-to-end ML pipelines (data ingestion, training, deployment, monitoring).
  • Implement and enhance MLOps practices for automation, CI/CD, and lifecycle management.
  • Write and optimize code in Python, SQL, or R for data processing and ML workflows.
  • Build and manage batch and streaming data pipelines using Spark, Kafka, or equivalent tools.
  • Collaborate with data scientists, engineers, and stakeholders to deploy ML solutions into production.
  • Apply data governance and quality checks to ensure secure and reliable delivery.
  • Recommend and implement data models to support BI, analytics, and campaign management.
  • Support migration activities, system improvements, and POCs for new technologies.

Qualifications

  • Diploma or Bachelor's degree in IT, Computer Science, Engineering, or related field.
  • Strong developer skills in Python, SQL, and R, with hands-on experience in ML/AI development.
  • Proficient in MLOps tools and concepts (CI/CD, Git, MLflow, Kubeflow, or similar).
  • Experience in data modeling, warehousing, and big data processing (Spark, Kafka).
  • Familiarity with Docker, Kubernetes, cloud ML services (AWS SageMaker, Azure ML, GCP Vertex AI).
  • Experience with BI tools (Power BI, Tableau).
  • Preferably with background in Cloudera, Snowflake, and banking/financial services.
  • Strong problem-solving, stakeholder management, and communication skills.

Why Join Us?

  • Hybrid setup (Ortigas, 2–3x onsite per month, day shift & mid shift).
  • Hands-on role with opportunities to build and deploy ML solutions in production.
  • Exposure to advanced AI/ML and data engineering technologies in the banking industry.

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