Senior Machine Learning Engineer (GCP)

Tiger Analytics; Canada; On-site; CAD 90,000 - 120,000; Full time

Job summary

A leading analytics firm is seeking a skilled Machine Learning Engineer to design and deploy scalable ML solutions. You will work with Google Cloud Platform and Vertex AI to develop and optimize ML models and integrate them into production environments. Key requirements include strong Python skills and experience in API development. This position offers excellent career growth in a dynamic environment.

Qualifications

• Hands-on experience with Google Cloud Platform (GCP) and Vertex AI.
• Strong skills in Python, OOP, and functional programming.
• Experience designing and deploying ML models in production.

Responsibilities

• Develop, train, and optimize ML models using Vertex AI.
• Design and build scalable ML pipelines for data processing.
• Deploy models using Vertex AI and integrate them with APIs.

Skills

Machine Learning with Vertex AI

Python programming

Data engineering

API Development

System Design

Tools

TensorFlow

PyTorch

Google Cloud Platform

scikit-learn

pandas

NumPy

PySpark

Job description

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.

Additional expertise required includes:

• Advanced Generative AI, including RAG with Graph-based hybrid retrieval and multimodal agents.
• Deep knowledge of ADK, Langchain Agentic Frameworks, fine-tuning, and distillation techniques.

Python expertise is essential, including:

• Strong OOP and functional programming skills.
• Proficiency with ML/DL libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy, PySpark.
• Experience with production-grade code, testing, and performance optimization.

GCP Cloud Architecture & Services proficiency includes:

• Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Pub/Sub, Dataproc, Dataflow.
• Understanding of IAM, VPC.

API Development & Integration skills include:

• Designing and building RESTful APIs using FastAPI or Flask.
• Integrating ML models into APIs for real-time inference.
• Implementing authentication, logging, and performance optimization.

System Design & Scalability experience involves:

• Designing end-to-end AI systems with scalability and fault tolerance.
• Developing distributed systems, microservices, and asynchronous processing.

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