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Canibuild Au Pty Ltd

Senior Machine Learning Developer (Remote)

Posted 5 Days Ago
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Remote
Hiring Remotely in Australia
Senior level
Remote
Hiring Remotely in Australia
Senior level
The Senior Machine Learning Developer will design, build, and optimize machine learning models for AI-driven site planning tools. Responsibilities include developing scalable ML solutions, optimizing real-time models, and collaborating with engineering teams to meet business needs.
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Description
About Us

Canibuild automates the residential construction industry’s design, approval, and sales processes, allowing clients to answer 'Can I build this on this plot of land?' instantly. As a fast-growing SaaS platform backed by Australia’s largest hedge fund, we serve clients across Australia, New Zealand, Canada, and the US.

Job Overview

The Senior Machine Learning Developer will design, build, and optimize machine learning models for Canibuild’s AI-driven site planning tools. This role involves developing scalable ML solutions, optimising real-time AI models, and collaborating with engineering teams. This role reports to the COO and Head of IT/Engineering.

Key Responsibilities

  • Model Development & Deployment: Design and deploy ML models, ensuring scalability and performance.
  • Data Pipeline Engineering: Develop efficient data pipelines for structured and unstructured data, including aerial imagery and geospatial datasets.
  • AI-driven Construction Intelligence: Build models to analyze and optimize construction site layouts and planning rules.
  • MLOps & Automation: Implement CI/CD workflows for ML, leveraging MLflow, Kubeflow, or similar tools.
  • Technical Leadership: Guide junior developers, conduct code reviews, and drive best practices in AI model development.
  • Collaboration: Work closely with data scientists, engineers, and stakeholders to translate business needs into AI solutions.
Requirements
  • Bachelor’s/Master’s in Computer Science, AI, or related field.
  • 5+ years in machine learning development.
  • Experience with TensorFlow, PyTorch, or scikit-learn.
  • Strong knowledge of cloud platforms (AWS, Azure, Google Cloud) and containerization (Docker, Kubernetes).
  • Familiarity with geospatial AI, computer vision, and big data technologies (Hadoop, Spark) is a plus.
Benefits
  • Flexible remote work opportunities with career development opportunities
  • Engagement with a supportive and collaborative global team
  • Competitive market based salary

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