Vertex AI
Tiger Analytics is looking for a skilled and innovative 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 play a key role in operationalizing machine learning models and driving the end-to-end ML lifecycle, from data ingestion to model serving and monitoring.
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.




Requirements 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
Benefits This position offers an excellent prospect for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

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📌 Senior Machine Learning Engineer (GCP) (Manitoba)
🏢 Tiger Analytics
📍 Manitoba