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Lead Data Scientist

Rivago Infotech Inc
Markham, Ontario, CAPosted April 2, 2026

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PythonSQLGCPDockerKubernetesBigQueryTensorFlowPyTorchscikit-learnCI/CDDevOps

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Job Description

Role : Lead AI/ML Engineer with GCP

Location : Remote

Hire type : Contract

End Client - Banking client

Implementation partner - ********

Exp - 10+

  • Detailed JD:
  • Responsible for designing, building, and deploying machine learning models and AI-driven systems within the Google Cloud ecosystem. This role bridges data science and software engineering, focusing on creating scalable, production-ready AI solutions—such as Generative AI, natural language processing, and predictive models—using tools like Vertex AI, TensorFlow, and BigQuery.

Key Responsibilities

  • Model Development & Training: Develop and train predictive and generative AI models using Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn, often within Vertex AI.
  • GCP Implementation: Implement solutions using GCP services like BigQuery, Dataflow, Cloud Functions, and Vertex AI Pipelines to build scalable infrastructure.
  • MLOps and Automation: Design and automate MLOps pipelines (training, deployment, monitoring) to ensure model performance, scalability, and reliability.
  • Data Engineering: Construct data pipelines for ingestion, preprocessing, and storage of structured/unstructured data using SQL and BigQuery.
  • Generative AI Integration: Implement LLMs, retrieval-augmented generation (RAG) patterns, and agentic workflows (e.g., using LangChain).
  • Optimization & Troubleshooting: Monitor and optimize deployed models for accuracy, latency, and cost-effectiveness.

Required Skills and Qualifications

  • Experience: 5+ years in AI/ML model deployment and software engineering.
  • Technical Proficiencies: Strong programming skills in Python and SQL.
  • GCP Expertise: Proven experience with Google Cloud Platform, specifically Vertex AI, Dataflow, and BigQuery.
  • ML Frameworks: In-depth knowledge of TensorFlow, PyTorch, or Scikit-learn.
  • DevOps/Containerization: Proficiency with Docker, Kubernetes (GKE), and CI/CD tools.
  • Education: Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field.

Preferred Qualifications

  • GCP Professional Machine Learning Engineer certification.
  • Experience with Vertex AI agent builder
  • Background in Natural Language Processing (NLP) or Computer Vision

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