Machine Learning Engineer

Job not on LinkedIn

🕒 July 14

🇵🇭 Philippines – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 28%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Pear Tree.

WebsiteLinkedInAll Job Openings

1 - 10 employees

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Pear Tree is a Melbourne‑born offshore recruitment and hiring services company that connects Australian, US, and UK businesses directly with skilled offshore professionals (primarily from the Philippines) without agency markups. They provide end-to-end hiring support — sourcing, screening, skills assessments, video interviews, reference checks — and offer payroll, Employer‑of‑Record, and compliance assistance plus a six‑month replacement guarantee. Pear Tree recruits across IT, sales & marketing, finance, creative, admin and operations roles, emphasizing cost savings, direct pay to talent, and secure onboarding workflows.

📋 Description

• 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