ML Platform Engineer – Google Cloud (GCP) and Vertex AI

Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!; Mississauga; On-site; CAD 80,000 - 110,000; Full time

Job summary

A technology solutions company in Mississauga is seeking a skilled MLOps Engineer to build and manage scalable machine learning pipelines on Google Cloud Platform. The role demands expertise in cloud platforms, machine learning engineering, automation scripting, and security compliance. You will be responsible for deploying solutions and enhancing monitoring capabilities using tools like TensorFlow and Kubernetes. Strong programming skills in Python and experience with CI/CD tools are essential. This position offers opportunities to impact innovative projects in a dynamic environment.

Qualifications

• Expertise in deploying and managing machine learning solutions on cloud platforms.
• Understanding of cloud services like Vertex AI, Cloud Storage, BigQuery.
• Proficient in automation and scripting using Python and SQL.

Responsibilities

• Build and manage scalable machine learning pipelines on GCP.
• Automate workflows for machine learning solutions.
• Monitor model performance and ensure compliance with security protocols.

Skills

Cloud platforms expertise

Machine learning engineering

Data pipelines

Automation scripting in Python

Version control with CI/CD

Kubernetes and Docker

Tools

Google Cloud Platform (GCP)

TensorFlow

Keras

PyTorch

scikit-learn

PySpark

Jenkins

Helm Charts

YAML

Prometheus

Grafana

Job description

Requirements

• Expertise in cloud platforms, ML engineering, data pipelines and CI/CD for deploying and managing machine learning solutions.


• Google Cloud Platform (GCP) services: AI Platform (Vertex AI), Cloud Storage, BigQuery, Cloud Functions, Cloud PubSub, Cloud Build, Airflow, and Cloud Run.


• Understanding of ML concepts and LLMs (training, validation, hyperparameter tuning, evaluation).


• Experience with TensorFlow, Keras, PyTorch, and scikit-learn.


• Data preprocessing, ETL, and data pipelines using PySpark and Scala using serverless dataproc.

CI/CD for ML (MLOps)

• Knowledge of CI/CD tools like Looper Pro and Jenkins.


• Model versioning, continuous training, and deployment using Vertex AI pipelines.

Automation Scripting

• Strong programming skills in Python, Bash, and SQL.


• Automation of workflows and ML pipelines.

DevOps Containerization

• Kubernetes (GKE) and Docker for containerization and orchestration.


• Good to have Helm charts and YAML for Kubernetes deployments.

Monitoring Observability

• Cloud Monitoring, Cloud Logging, Prometheus and Grafana for monitoring and alerting.


• Model performance monitoring with Vertex AI Model Monitoring.

Security Compliance

• Understanding of VPC, firewall rules, and service accounts.

Data Science

• Must understand general data science methods and the development life cycle.

An MLOps Engineer responsible for building, automating, and managing scalable machine learning pipelines and deployments on Google Cloud Platform.