Senior ML Engineer — GCP & Vertex AI Architect

Tiger Analytics; Canada; Remote; CAD 90,000 - 140,000; Full time

Job summary

Tiger Analytics seeks a skilled Machine Learning Engineer with hands-on experience in Google Cloud Platform (GCP) and Vertex AI to design, build, and deploy scalable ML solutions. You will operationalize models across data ingestion to serving and monitoring.

You will collaborate with data scientists and engineers to implement end-to-end ML pipelines, apply CI/CD for models, and ensure governance, security, and explainability within Vertex AI.

Qualifications

• Advanced Generative AI
• Advanced RAG including Graph based hybrid retrieval
• Multimodal agent
• Deep knowledge on ADK , Langchain Agentic Frameworks
• Fine tuning and Distillation
• Python Expertise
• Expert in Python with strong OOP and functional programming skills
• Proficient in ML/DL libraries: TensorFlow, PyTorch, scikit-learn, pandas, NumPy, PySpark
• Experience with production-grade code, testing, and performance optimization
• GCP Cloud Architecture & Services
• Proficiency in GCP services such as Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Pub/Sub, Dataproc, Dataflow
• Understanding of IAM, VPC
• API Development & Integration
• Designs and builds RESTful APIs using FastAPI or Flask
• Integrates ML models into APIs for real-time inference
• Implements authentication, logging, and performance optimization
• System Design & Scalability
• Designs end-to-end AI systems with scalability and fault tolerance in mind
• Hands-on experience in developing distributed systems, microservices, and asynchronous processing

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.

Skills

Python expertise

ML pipelines

GCP Vertex AI

TensorFlow

PyTorch

REST APIs

CI/CD

BigQuery

Dataflow

Tools

Vertex AI

Cloud Run

Dataflow

Pub/Sub

Job description

Tiger Analytics seeks a skilled Machine Learning Engineer with hands-on experience in Google Cloud Platform (GCP) and Vertex AI to design, build, and deploy scalable ML solutions. You will operationalize models across data ingestion to serving and monitoring.

You will collaborate with data scientists and engineers to implement end-to-end ML pipelines, apply CI/CD for models, and ensure governance, security, and explainability within Vertex AI.