Tiger Analytics
Senior Machine Learning Engineer (GCP)
Remote Machine Learning Engineer role with clear candidate location fit.
PostedJun 21, 2026
Eligible countries1 accepted country
Seniority signalSenior
Work settingRemote
Accepted candidate locations
Canada
Role overview
Senior Machine Learning Engineer (GCP)
Requirements and responsibilities
Readable role content extracted into sections for faster review.
Key Responsibilities:
- Develop, train, and optimize ML models using Vertex AI, including Vertex Pipelines, AutoML, and custom model training.
- Design and build scalable ML pipelines for feature engineering, training, evaluation, and deployment.
- Deploy models to production using Vertex AI endpoints and integrate with downstream applications or APIs.
- Collaborate with data scientists, data engineers, and MLOps teams to enable reproducible and reliable ML workflows.
- Monitor model performance and set up alerting, retraining triggers, and drift detection mechanisms.
- Utilize GCP services such as BigQuery, Dataflow, Cloud Functions, Pub/Sub, and GCS in ML workflows.
- Apply CI/CD principles to ML models using Vertex AI Pipelines, Cloud Build, and GitOps practices.
- Implement model governance, versioning, explainability, and security best practices within Vertex AI.
- Document architecture decisions, workflows, and model lifecycle clearly for internal stakeholders.
- Multimodal agent
- Deep knowledge on ADK , Langchain Agentic Frameworks
- Fine tuning and Distillation
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