Machine Learning Engineer (with Vertex AI Experience)

Tiger Analytics; Canada; On-site; CAD 85,000 - 120,000; Full time

Job summary

A leading analytics firm in Canada is seeking a skilled Machine Learning Engineer to design, build, and deploy scalable ML solutions. The role involves optimizing ML models with Vertex AI, utilizing GCP services, and developing APIs for real-time inference. Candidates should have deep knowledge of Python, advanced generative AI, and a passion for building innovative solutions. This position offers significant career development opportunities in a fast-paced environment.

Benefits

Significant career development opportunities

Entrepreneurial environment

High degree of individual responsibility

Qualifications

• Hands-on experience with Google Cloud Platform (GCP) and Vertex AI.
• Expert in Python with strong OOP and functional programming skills.
• Deep knowledge of advanced generative AI.
• Strong understanding of GCP cloud architecture.

Responsibilities

• Develop, train, and optimize ML models using Vertex AI.
• Design and build scalable ML pipelines.
• Deploy models to production and integrate with APIs.
• Collaborate with various teams for ML workflows.

Skills

Machine Learning

Python

Google Cloud Platform (GCP)

Vertex AI

TensorFlow

PyTorch

scikit-learn

BigQuery

Flask

FastAPI

Tools

Vertex Pipelines

Cloud Functions

Pub/Sub

Cloud Storage

Dataflow

Docker

Job description

Overview

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.

Advanced Generative AI

• 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

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.