MLOps Engineer

Role name MLOps Engineer

Location - Mississauga 2 or 3 days hybrid

Duration - Contract

Exp Level - 7+ years

Role Description s:

Essential

Skills:

Expertise in cloud platforms| ML engineering| data pipelines| and CICD for deploying and managing machine learning solutions.

Skill required

1.Cloud Platforms Services (Google Cloud) google Cloud Platform (GCP) services AI Platform (Vertex AI)| Cloud Storage| Big Query| Cloud Functions| Cloud Pub Sub| Cloud Build| Airflow| and Cloud Run. Element Platform visibility

2.ML Data Engineeringo Understanding of ML concepts and LLMs (training| validation| hyperparameter tuning| evaluation).experience with Tensor Flow| Keras| PyTorch| and scikit-learn. Data preprocessing| ETL| and data pipelines using pyspark

Scala using serverless dataproc

3.CICD for ML (MLOps) knowledge of CICD tools Looper pro Jenkins. Model versioning| continuous training| and deployment using Vertex AI pipelines.

4.Automation Scripting. Strong programming skills in Python| Bash| and SQL automation of workflows and ML pipelines.

5.Dev Ops Containerization Kubernetes (GKE) and Docker for containerization and orchestration. Good to have Helm charts and YAML for Kubernetes deployments.

6.Monitoring Observability Cloud Monitoring| Cloud Logging| Prometheus| and Grafana for monitoring and alerting. Model performance monitoring with Vertex AI Model Monitoring.

7.Security Compliance Understanding of VPC| firewall rules| and service accounts. Managing secrets using Secret Manager.

8.Data Science Must understand general data science methods and the development life cycle

An ML Ops Engineer responsible for building| automating| and managing scalable machine learning pipelines and deployments on Google Cloud Platform.

Regards,

Email:

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