AI Engineering: Data

4 days ago

Taguig, Philippines Yondu, Inc. Full time

Yondu, Inc. Taguig, National Capital Region, Philippines

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Join to apply for the AI Engineering: Data & MLOps Engineer. role at Yondu, Inc.

Yondu, Inc. Taguig, National Capital Region, Philippines

3 weeks ago Be among the first 25 applicants

Join to apply for the AI Engineering: Data & MLOps Engineer. role at Yondu, Inc.

  • Build and manage scalable data pipelines for structured and unstructured data, ensuring data quality, integrity, and availability.
  • Design, implement, and maintain MLOps workflows for training, testing, deploying, and monitoring machine learning models.
  • Collaborate with data scientists and ML engineers to automate end-to-end machine learning lifecycle processes (CI/CD/CT for ML).
  • Develop and manage feature stores, model registries, and metadata tracking tools.
  • Ensure system reliability and performance using logging, monitoring, and alerting tools.
  • Support infrastructure-as-code (IaC) and cloud automation for model training and inference environments.
  • Integrate ML models into production systems using containers (Docker), orchestration tools (Kubernetes), and cloud services.
  • Build and manage scalable data pipelines for structured and unstructured data, ensuring data quality, integrity, and availability.
  • Design, implement, and maintain MLOps workflows for training, testing, deploying, and monitoring machine learning models.
  • Collaborate with data scientists and ML engineers to automate end-to-end machine learning lifecycle processes (CI/CD/CT for ML).
  • Develop and manage feature stores, model registries, and metadata tracking tools.
  • Ensure system reliability and performance using logging, monitoring, and alerting tools.
  • Support infrastructure-as-code (IaC) and cloud automation for model training and inference environments.
  • Integrate ML models into production systems using containers (Docker), orchestration tools (Kubernetes), and cloud services.
Minimum Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
  • 3+ years of experience in data engineering, DevOps, or MLOps roles.
  • Strong programming skills in Python, with experience in libraries such as Pandas, MLflow, Airflow, and PyTorch/TensorFlow.
  • Hands-on experience with cloud platforms (AWS, GCP, or Azure) and services such as S3, Lambda, SageMaker, Vertex AI, or Databricks.
  • Familiarity with CI/CD tools (e.g., GitHub Actions, Jenkins, ArgoCD) and containerization (Docker, Kubernetes).
  • Solid understanding of data formats, ETL frameworks, and scalable storage systems.
Preferred Qualifications
  • Experience with model versioning, A/B testing, and continuous training in production.
  • Familiarity with modern data stack tools (e.g., dbt, Kafka, Snowflake, Redshift).
  • Knowledge of security best practices in handling sensitive data and models.
  • Certification in cloud technologies (e.g., AWS Certified Machine Learning, Google Cloud ML Engineer).
Seniority level
  • Seniority level Entry level
Employment type
  • Employment type Full-time
Job function
  • Job function Information Technology

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