Note: This is for active pooling purposes only. Submitting your application does not guarantee employment. Your details will be kept on file and considered for future opportunities as they become available.We are seeking a dedicated and organized Machine Learning Engineer to join our team at D2B. In this remote role, you'll work closely with engineering and AI teams to design, build and deploy production-grade machine learning solutions that solve real-world construction challenges.This is a hands-on engineering role suited to someone who enjoys taking ML models from concept through to production while working in a collaborative, remote-first environment.Key Responsibilities: Design, develop, and deploy production-ready machine learning models with a strong focus on computer vision applications. Build AI capabilities that identify, track, and analyse construction progress from visual data. Research, prototype, and implement solutions using LLMs, multimodal AI models, and generative AI technologies. Evaluate when to leverage commercial foundation models versus developing custom machine learning solutions. Design, build, and maintain scalable ML pipelines covering data collection, labelling, training, evaluation, deployment, and monitoring. Source, clean, curate, and prepare high-quality datasets for model training. Develop and maintain MLOps infrastructure, including model versioning, CI/CD pipelines, deployment automation, and monitoring. Collaborate with Software Engineers, Product Managers, and AI specialists to integrate machine learning capabilities into production applications. Optimise model accuracy, inference performance, scalability, and reliability. Stay current with emerging machine learning techniques, AI frameworks, and industry best practices. Requirements Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related discipline. 3+ years of commercial experience as a Machine Learning Engineer or AI Engineer. Proven experience building and deploying production machine learning systems. Strong experience developing computer vision models. Experience with end-to-end MLOps, including: Data collection and labelling Model training and evaluation Pipeline development CI/CD automation Model versioning Monitoring and optimisation Experience working with LLMs, multimodal AI models, and generative AI technologies. Strong Python development skills. Experience using deep learning frameworks such as PyTorch. Experience deploying scalable inference infrastructure. Strong understanding of the software development lifecycle. Excellent written and verbal English communication skills. Comfortable working remotely with distributed teams across New Zealand and Australia. Highly Desirable Experience with TensorRT or similar inference optimisation engines. Experience developing Edge AI or Edge ML applications. Experience with .NET and C#. Experience working with AWS, Azure, or Google Cloud Platform. Experience with Docker, Kubernetes, and modern ML deployment pipelines. Experience working with construction technology, geospatial imaging, drone imagery, or spatial data. BenefitsCompetitive salary based on experience and skill set100% remote role — work from home anywhere in the PhilippinesPaid local holidays aligned with the Australian business calendarOpportunities for training and professional growthWork directly with a supportive Australian team — no agency middlemanLong-term engagement with a stable and growing business
Note: This is for active pooling purposes only. Submitting your application does not guarantee employment. Your details will be kept on file and considered for future opportunities as they become available.
We are seeking a dedicated and organized Machine Learning Engineer to join our team at D2B. In this remote role, you'll work closely with engineering and AI teams to design, build and deploy production-grade machine learning solutions that solve real-world construction challenges.
This is a hands-on engineering role suited to someone who enjoys taking ML models from concept through to production while working in a collaborative, remote-first environment.
Key Responsibilities:
- Design, develop, and deploy production-ready machine learning models with a strong focus on computer vision applications.
- Build AI capabilities that identify, track, and analyse construction progress from visual data.
- Research, prototype, and implement solutions using LLMs, multimodal AI models, and generative AI technologies.
- Evaluate when to leverage commercial foundation models versus developing custom machine learning solutions.
- Design, build, and maintain scalable ML pipelines covering data collection, labelling, training, evaluation, deployment, and monitoring.
- Source, clean, curate, and prepare high-quality datasets for model training.
- Develop and maintain MLOps infrastructure, including model versioning, CI/CD pipelines, deployment automation, and monitoring.
- Collaborate with Software Engineers, Product Managers, and AI specialists to integrate machine learning capabilities into production applications.
- Optimise model accuracy, inference performance, scalability, and reliability.
- Stay current with emerging machine learning techniques, AI frameworks, and industry best practices.
Requirements
- Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related discipline.
- 3+ years of commercial experience as a Machine Learning Engineer or AI Engineer.
- Proven experience building and deploying production machine learning systems.
- Strong experience developing computer vision models.
- Experience with end-to-end MLOps, including:
- Data collection and labelling
- Model training and evaluation
- Pipeline development
- CI/CD automation
- Model versioning
- Monitoring and optimisation
-
- Experience working with LLMs, multimodal AI models, and generative AI technologies.
- Strong Python development skills.
- Experience using deep learning frameworks such as PyTorch.
- Experience deploying scalable inference infrastructure.
- Strong understanding of the software development lifecycle.
- Excellent written and verbal English communication skills.
- Comfortable working remotely with distributed teams across New Zealand and Australia.
Highly Desirable
- Experience with TensorRT or similar inference optimisation engines.
- Experience developing Edge AI or Edge ML applications.
- Experience with .NET and C#.
- Experience working with AWS, Azure, or Google Cloud Platform.
- Experience with Docker, Kubernetes, and modern ML deployment pipelines.
- Experience working with construction technology, geospatial imaging, drone imagery, or spatial data.
Benefits
- Competitive salary based on experience and skill set
- 100% remote role — work from home anywhere in the Philippines
- Paid local holidays aligned with the Australian business calendar
- Opportunities for training and professional growth
- Work directly with a supportive Australian team — no agency middleman
- Long-term engagement with a stable and growing business
