canibuild

• Own end-to-end paid/digital media and SEO as a relentless individual contributor driving Canibuild's global pipeline growth. • This role demands a data-obsessed operator who uses analytics to generate Sales Qualified Leads (SQLs) and Quality Leads — not just traffic. • Own technical SEO, on-page optimisation, and keyword strategy across all markets. • Build and maintain content briefs aligned to bottom-of-funnel intent to drive SQLs. • Track organic rankings, Core Web Vitals, and crawl health via GA4 and Search Console. • Coordinate with content and dev teams to implement SEO fixes and content calendars. • Plan, launch, and optimise campaigns across Meta, Google (Search/Display/YouTube), LinkedIn, and programmatic channels. • Manage budgets and agency/vendor relationships with a focus on ROAS and CPL efficiency. • Leverage AI-native tools (e.g. Performance Max, Advantage+, automated bidding, generative ad creative) to lead — not just manage — paid media. • Creative problem-solving with lean budgets; make every dollar demonstrate measurable SQL impact. • Own performance dashboards in HubSpot, GA4, and BI tools — self-serve, no waiting on analysts. • Track and report on CTR, CPL, LTV, ROAS, SQL volume, and Quality Lead rate weekly. • Use attribution modelling to assess channel contribution and inform budget decisions. • Comfortable with SQL-based reporting and data exports; ties every initiative to pipeline outcomes. • Stay current with AI-powered marketing tools and proactively test and implement new capabilities. • Lead prompt-engineered creative workflows, AI-assisted audience targeting, and automated reporting. • Build a personal toolkit of AI tools that multiplies individual output — this is an IC role, not a management role. • Partner with Sales, Product, Content, and Design on campaign briefs and aligned deliverables. • Own project briefs, timelines, task assignments, and stakeholder communications autonomously. • A/B test creative, copy, channels, and audience segments continuously. • Architect and administer HubSpot: contact segmentation, lead scoring, workflows, and dashboards. • Design email nurture tracks and drip campaigns that convert MQLs to SQLs. • Maintain CRM hygiene and ensure data integrity across the funnel.

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 We are looking for a Machine Learning Engineer with strong experience in Computer Vision and document understanding to help build AI-driven capabilities within our property technology platform. The role focuses on developing models that analyze visual and document-based data to extract structured information and support automated decision-making within our products. You will work closely with product and engineering teams to design, build, and deploy machine learning solutions that operate reliably in production environments. We are particularly interested in engineers who have taken machine learning systems from experimentation to production and are comfortable solving messy real-world data problems. Key Responsibilities - Design, develop, and deploy computer vision and machine learning models for analyzing visual and document-based data. - Build pipelines that convert unstructured visual inputs into structured and usable information. - Develop and evaluate models for tasks such as object detection, segmentation, document parsing, and image understanding. - Apply OCR and related techniques to extract meaningful information from complex documents and imagery. - Work with large datasets and build efficient training and evaluation pipelines. - Handle real-world visual datasets that may contain noise, inconsistencies, incomplete information, or varying formats. - Experiment with different approaches to solve challenging computer vision problems and evaluate tradeoffs between accuracy, performance, and complexity. - Collaborate with product and engineering teams to integrate machine learning models into scalable production systems. - Continuously improve model performance, accuracy, and robustness in real-world environments. - Stay up to date with the latest developments in AI and computer vision and apply relevant techniques where appropriate. - Actively leverage modern AI tools and frameworks to accelerate experimentation, development, and engineering workflows. Requirements - 5+ years of hands-on experience building and deploying machine learning models, particularly in Computer Vision or document understanding. - Strong proficiency in Python for machine learning and data processing. - Hands-on experience with modern ML frameworks such as PyTorch and libraries in the Hugging Face ecosystem. - Experience with computer vision tooling such as OpenCV. - Experience with common ML and data science libraries such as scikit-learn, NumPy, and Pandas. - Experience developing models for tasks such as segmentation, object detection, or document analysis. - Experience working with large image datasets and building training pipelines. - Solid understanding of model evaluation, data preprocessing, and performance optimization. - Strong problem-solving skills and ability to work in a fast-paced product environment. - Ability to collaborate effectively with cross-functional engineering and product teams. - The candidate should be based in Australia - Willing to work remotely full-time - Work schedule is Mon to Fri, 9:00 AM to 5:00 PM AEST Preferred Qualifications - Experience with TensorFlow or other deep learning frameworks. - Experience working with OCR pipelines or document analysis systems. - Experience deploying machine learning models in production environments. - Experience with containerized deployments such as Docker or Kubernetes. - Experience working with complex technical documents, diagrams, or structured visual data. - Familiarity with spatial or geometry-related data problems. - Experience with libraries such as Detectron2, MMDetection, or similar. - Familiarity with frameworks used to integrate modern AI models into applications (e.g., LangChain or similar tooling). - Contributions to open-source ML or computer vision projects are a plus. Additional Information - The problems we work on involve complex visual and document-based data, so we value engineers who enjoy tackling challenging technical problems and experimenting with different approaches to reach practical solutions. - Candidates are required to include link to relevant projects, GitHub repositories, research work, or examples of machine learning systems they have built. Benefits - Flexible remote work opportunities with career development opportunities - Engagement with a supportive and collaborative global team - Competitive market based salary

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 We are looking for a Machine Learning Engineer with strong experience in Computer Vision and document understanding to help build AI-driven capabilities within our property technology platform. The role focuses on developing models that analyze visual and document-based data to extract structured information and support automated decision-making within our products. You will work closely with product and engineering teams to design, build, and deploy machine learning solutions that operate reliably in production environments. We are particularly interested in engineers who have taken machine learning systems from experimentation to production and are comfortable solving messy real-world data problems. Key Responsibilities - Design, develop, and deploy computer vision and machine learning models for analyzing visual and document-based data. - Build pipelines that convert unstructured visual inputs into structured and usable information. - Develop and evaluate models for tasks such as object detection, segmentation, document parsing, and image understanding. - Apply OCR and related techniques to extract meaningful information from complex documents and imagery. - Work with large datasets and build efficient training and evaluation pipelines. - Handle real-world visual datasets that may contain noise, inconsistencies, incomplete information, or varying formats. - Experiment with different approaches to solve challenging computer vision problems and evaluate tradeoffs between accuracy, performance, and complexity. - Collaborate with product and engineering teams to integrate machine learning models into scalable production systems. - Continuously improve model performance, accuracy, and robustness in real-world environments. - Stay up to date with the latest developments in AI and computer vision and apply relevant techniques where appropriate. - Actively leverage modern AI tools and frameworks to accelerate experimentation, development, and engineering workflows. Requirements - 5+ years of hands-on experience building and deploying machine learning models, particularly in Computer Vision or document understanding. - Strong proficiency in Python for machine learning and data processing. - Hands-on experience with modern ML frameworks such as PyTorch and libraries in the Hugging Face ecosystem. - Experience with computer vision tooling such as OpenCV. - Experience with common ML and data science libraries such as scikit-learn, NumPy, and Pandas. - Experience developing models for tasks such as segmentation, object detection, or document analysis. - Experience working with large image datasets and building training pipelines. - Solid understanding of model evaluation, data preprocessing, and performance optimization. - Strong problem-solving skills and ability to work in a fast-paced product environment. - Ability to collaborate effectively with cross-functional engineering and product teams. - The candidate should be based in India - Willing to work remotely full-time - Work schedule is Mon to Fri, 3:30am to 12:30pm IST Preferred Qualifications - Experience with TensorFlow or other deep learning frameworks. - Experience working with OCR pipelines or document analysis systems. - Experience deploying machine learning models in production environments. - Experience with containerized deployments such as Docker or Kubernetes. - Experience working with complex technical documents, diagrams, or structured visual data. - Familiarity with spatial or geometry-related data problems. - Experience with libraries such as Detectron2, MMDetection, or similar. - Familiarity with frameworks used to integrate modern AI models into applications (e.g., LangChain or similar tooling). - Contributions to open-source ML or computer vision projects are a plus. Additional Information - The problems we work on involve complex visual and document-based data, so we value engineers who enjoy tackling challenging technical problems and experimenting with different approaches to reach practical solutions. - Candidates are required to include links to relevant projects, GitHub repositories, research work, or examples of machine learning systems they have built. Benefits - Flexible remote work opportunities with career development opportunities - Engagement with a supportive and collaborative global team - Competitive market based salary

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We’re looking for GIS interns with basic GIS knowledge to join our 3-month program at Canibuild. - Hands-on GIS & urban planning experience - Work with real project data and tools - Guidance from experienced mentors Qualifications - Students or graduates in GIS or related fields. Benefits - Opportunities for career growth. - A collaborative, fast-paced, and innovative culture that values initiative, ownership, and smart solutions. - A remote-first environment with global collaboration. Company Description Canibuild is the proptech company transforming how people plan and start construction projects, whether you’re a government agency, builder or property owner. With over 1 million site assessments completed and 8,500+ clients across the US, ANZ and CA, Canibuild’s AI-powered platform delivers instant site feasibility, automated pre-permitting, and real-time 3D visualization for homes, ADUs, pools, sheds, garages, and more. From zoning checks to public inquiries and the digitization of planning workflows, Canibuild simplifies compliance and planning for everyone. We’re redefining how the world builds. Learn more at canibuild.com.

Role Description We’re looking for a Senior Product Manager to own Canibuild’s Subscription & Platform Operations domain. This role is responsible for the systems that power our SaaS subscription lifecycle, including: - Billing - Plan management - Account provisioning - Operational automation A core part of this role is owning and evolving our subscription and billing platform (Stripe Billing / Chargebee) and ensuring it integrates cleanly with our product, CRM, and operational workflows. You will work closely with: - Engineering - Finance - Operations - Support - Sales This is a high-ownership role with clear accountability for the health of our subscription platform and internal operational tooling. Qualifications - 5+ years experience as a Product Manager in a SaaS product company - Direct experience owning a subscription or billing platform - Hands-on experience with Stripe Billing, Chargebee, or similar subscription systems - Experience managing subscription lifecycle workflows (trial, upgrade, downgrade, cancellation) - Experience working closely with engineers on technical integrations and system design - Strong ownership mindset and ability to operate in ambiguity - Clear written communication and structured reporting Requirements - Experience working with SaaS pricing models and subscription management - Experience building internal admin tools or operational platforms - Familiarity with the operational complexity behind billing, CRM, and finance system integrations What We’re Looking For - Outcome-focused and comfortable prioritising under constraints - Comfortable running discovery with internal stakeholders (Ops, Support, Finance, Sales) - Dynamic, proactive, and able to move from problem to execution quickly - Comfortable working in a fast-paced environment where priorities can shift Benefits - Competitive salary, benefits, and opportunities for growth - A collaborative, fast-paced, and innovative culture that values initiative, ownership and smart solutions - A remote-first environment with global collaboration