Canibuild Au Pty Ltd
Data Scientist / Machine Learning Engineer (Remote)
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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 OverviewWe are seeking a highly skilled Data Scientist / ML Engineer across levels with a strong background in Natural Language Processing (NLP) and Computer Vision. The ideal candidate should have 4+ years of experience working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vision-Language Models (VLMs), and segmentation techniques. You will work closely with our product and engineering teams to develop and deploy AI-driven solutions that enhance our property-tech ecosystem.
Key Responsibilities- Design, develop, and deploy machine learning models focused on NLP and Computer Vision for property-related applications.
- Implement and fine-tune LLMs for tasks such as document processing, chatbot automation, and property insights.
- Build and optimize RAG pipelines to improve the accuracy and relevance of information retrieval in real estate data.
- Develop computer vision models for segmentation, object detection, and VLM applications to enhance image and video analysis.
- Work with structured and unstructured real estate data, including property listings, legal documents, and geospatial data.
- Collaborate with cross-functional teams to integrate AI models into scalable production systems.
- Stay up to date with the latest advancements in AI research and apply best practices to solve real-world challenges.
- Optimize models for performance, efficiency, and deployment in cloud and edge environments.
- 5+ years of hands-on experience in building and deploying ML models in NLP (LLMs, RAGs) and Computer Vision (segmentation, Vision Language Models).
- Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Hugging Face, and OpenCV.
- Experience working with vector databases, embedding models, and information retrieval techniques.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps best practices.
- Solid understanding of data preprocessing, model evaluation, and performance optimization techniques.
- Experience with multimodal AI models and working with large-scale datasets.
- Strong problem-solving skills and ability to work in a fast-paced, dynamic environment.
- Excellent communication skills and a passion for leveraging AI to transform the property-tech industry.
Preferred qualifications
- Experience in deploying models using containerization (Docker, Kubernetes) and microservices architectures.
- Familiarity with GIS data processing and spatial analytics.
- Contributions to open-source AI/ML projects or research publications in NLP/Computer Vision.
- Flexible remote work opportunities with career development opportunities
- Engagement with a supportive and collaborative global team
- Competitive market based salary
What you need to know about the Melbourne Tech Scene
Home to 650 biotech companies, 10 major research institutes and nine universities, Melbourne is among one of the top cities for biotech. In fact, some of the greatest medical advancements were conceptualized and developed here, including Symex Lab's "lab-on-a-chip" solution that monitors hormones to predict ovulation for conception, and Denteric's vaccine for periodontal gum disease. Yet, the thousands of people working in the city's healthtech sector are just getting started, to say nothing of the tech advancements across all other sectors.
