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Machine Learning Consultant

Apptoza Inc.
Be an Early ApplicantContractmidHybrid
CAPosted March 12, 2026

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PythonScalaBashSQLGCPDockerKubernetesJenkinsBigQueryAirflowTensorFlowPyTorchscikit-learnCI/CDDevOps

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Job Description

Hi,

Hope you are doing Great.

We are looking for a highly skilled ML Ops Engineer with strong expertise in Google Cloud Platform, Vertex AI, and ML pipeline deployment.

Must have hands-on experience with Python, CI/CD (e.g., Jenkins), and containerization using Docker and Kubernetes.

📢 Hiring: ML Ops Engineer (GCP)

Location : MISSISSAUGA, ON (Hybrid : 3days onsite in a week)

Contract : 6months

Experience Required: 6-8 Years

Job Description: Role Descriptions: Expertise in cloud platforms| ML engineering| data pipelines| and CICD for deploying and managing machine learning solutions. Skill required1.Cloud Platforms Services (Google Cloud) Google Cloud Platform (GCP) services AI Platform (Vertex AI)| Cloud Storage| Big Query| Cloud Functions| Cloud PubSub| Cloud Build| Airflow| and Cloud Run. Element Platform visibility 2.ML Data Engineering Understanding of ML concepts and LLMs (training| validation| hyperparameter tuning| evaluation). Experience with TensorFlow| Keras| PyTorch| and scikit-learn. Data pre-processing| 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.DevOps 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 cycleAn ML Ops Engineer responsible for building| automating| and managing scalable machine learning pipelines and deployments on Google Cloud Platform.

Keyword:

Skills: #MLOps, #MachineLearning, #GCP, #VertexAI, #Python, #TensorFlow, #PyTorch, #Docker, #Kubernetes, #BigQuery, #Airflow, #Jenkins

Regards

Rakesh Ummadi

Apptoza Inc

647-557-6949

Rakesh@apptoza.com

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