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Senior Machine Learning Engineer

Careers · Colombo

New
Senior 🇬🇧 English
Snowflake Snowpark Apache Airflow GitLab CI GitHub Actions Kubernetes Docker Terraform FastAPI gRPC Prometheus Grafana Evidently AI LightGBM XGBoost TensorFlow PyTorch Python SQL

Job description

About the role

The Senior Machine Learning Engineer is responsible for designing, building and operating a unified machine learning infrastructure that standardises the model lifecycle from research to production. The role bridges the gap between batch-oriented data in Snowflake and real-time inference on Kubernetes, applying high software engineering standards and reducing implementation redundancy across data science squads.

Key responsibilities

  • Design and maintain the core ML platform architecture, integrating Snowflake/Snowpark with Kubernetes for hybrid workloads.
  • Deliver end-to-end data science products such as flight revenue forecasting, customer retention and ground operations.
  • Automate ML pipelines covering data ingestion, model training and continuous deployment with Apache Airflow and GitLab CI/GitHub Actions.
  • Build and manage a centralised Feature Store and Model Registry in Snowflake.
  • Implement observability for model performance, data drift and system health using Prometheus, Grafana and Evidently AI.
  • Develop reusable FastAPI or gRPC service wrappers for real-time model serving.
  • Set up "paved road" workflows (CI/CD, unit testing, modular code) for the wider data science team.

Required profile

  • Bachelor's or Master's degree in Computer Science, Software Engineering or a related field; fluent English.
  • Minimum 6-8 years of experience in data science, MLOps, platform engineering or DevOps for machine learning, including 1-2 years in the aviation domain (airline or vendor).
  • Deep understanding of aviation systems such as PNRs, e-tickets and revenue management logic (yield and inventory control).
  • Ability to influence architectural decisions and engineering culture without direct authority.

Required skills

  • Mastery of Kubernetes, Docker and Infrastructure as Code (Terraform)
  • Expert Python (OOP, modular design) and SQL
  • Serving models with LightGBM, XGBoost, TensorFlow and PyTorch
  • Hands-on experience with Snowflake/Snowpark and Airflow
  • Proficiency in MS Office

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Source : ats:successfactors

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Published 1 day ago

Expires 1 month from now

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