ML Ops Engineer

Skills

Job Specifications

About Role:

We are looking for an ML Ops Engineer to build, automate, and manage machine learning pipelines on Google Cloud.

Key Responsibilities:

Develop and deploy ML models using Google Cloud (GCP) services like Vertex AI, BigQuery, Cloud Storage, and Cloud Run.
Build and manage data pipelines and ETL processes.
Handle CI/CD for ML models (model versioning, training, and deployment).
Write automation scripts using Python, Bash, and SQL.
Use Docker and Kubernetes (GKE) for containerization and deployment.
Monitor systems and model performance.
Ensure security using VPC, firewall rules, and secret management.

Required Skills:

Strong knowledge of ML concepts and tools (TensorFlow, PyTorch, scikit-learn).
Experience with data engineering and cloud platforms (GCP).
Understanding of MLOps and DevOps practices.

About the Company

We accelerate business transformation by solving complex technology, business and talent challenges. A digital transformation Partner and Global consulting firm transforming clients business, operating and technology models for the digital era. Strong experience to support the industry providing change management and business process improvement services with a specialist knowledge in Procurement, Supply Chain and Logistics. Know more

Related Jobs

Company Name

Pacer Group

Job Title

Google Cloud Engineer

Toronto, Canada

Hybrid

Freelance

15-03-2026

Company Name

Aarorn Technologies Inc

Job Title

GCP Cloud Engineer

Toronto, Canada

Hybrid

Freelance

16-02-2026