Machine Learning Engineer

Pear Tree.

Machine Learning Engineer designing AI solutions for construction challenges at D2B. Collaborating with engineering and AI teams in a remote-first environment.

Posted 7/14/2026full-timeRemote • 🇵🇭 PhilippinesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, developing, and deploying machine learning models with a focus on computer vision and MLOps. Proficient in leveraging AI technologies, including LLMs and generative AI, while ensuring model accuracy and performance in production environments.

Highest-signal resume keywords

Machine Learning EngineeringComputer Vision Model DevelopmentMLOps Infrastructure ManagementPython DevelopmentDeep Learning Frameworks (PyTorch)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningComputer VisionMLOpsData CollectionModel TrainingCI/CD AutomationModel VersioningMonitoringDeep Learning (PyTorch)Inference Optimization

Soft Skills

Excellent Communication SkillsCollaboration

Tools & Technologies

AWSAzureGoogle Cloud PlatformDockerKubernetesTensorRT

Industry Keywords

Construction TechnologyGeospatial ImagingDrone ImagerySpatial Data

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetes.NETPythonPyTorch

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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