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Machine Learning Engineer (with Vertex AI Experience)

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Onsite

Machine Learning Engineer (with Vertex AI Experience)

Tiger Analytics

Machine Learning Engineer (with Vertex AI Experience)

Skills

Google Cloud PlatformFlaskPythonMicroservicesNumPypandasPyTorchTensorFlowMachine LearningAIFastAPIPySpark

2 months ago

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Important information


Contract type:

Permanent

Location:

Canada

Work mode:

Onsite

Published on:

17 August 2026

What they need


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 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.

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