AP - Machine Learning Engineer

Promptcube3; Philippines; On-site; PHP 2,009,000 - 3,571,000; Full time

Benefits offered by this job

100% remote

Paid AU calendar holidays

Training opportunities

Job summary

PromptCube is seeking a dedicated Machine Learning Engineer to design, build, and deploy production-grade ML solutions for construction challenges in a remote-first environment.

You will work with engineering and AI teams to handle data pipelines, model training, deployment, and monitoring, using PyTorch and modern MLOps practices. Strong English is essential for global collaboration.

Qualifications

• 3+ years of commercial experience as a Machine Learning Engineer or AI Engineer.
• Experience building and deploying production ML systems.
• Strong Python development skills and PyTorch experience.
• Experience with end-to-end MLOps (data labeling, training, CI/CD, monitoring).
• Experience with LLMs, multimodal models, and generative AI.
• Excellent English communication; remote work with distributed teams.

Responsibilities

• Design, develop, and deploy production-ready ML models for computer vision.
• Build AI capabilities to identify and analyse construction progress from visual data.
• Prototype and implement LLMs, multimodal AI, and generative AI solutions.
• Develop scalable ML pipelines: data collection, labeling, training, evaluation, deployment, monitoring.
• Maintain MLOps infrastructure: versioning, deployment automation, monitoring.
• Collaborate with Software Engineers, PMs, AI specialists to integrate ML into prod apps.
• Optimize accuracy, inference performance, scalability, reliability.
• Stay current with emerging ML techniques and frameworks.

Skills

Python

PyTorch

Docker

Kubernetes

MLOps

Computer Vision

Edge AI

Education

Bachelor's degree in Computer Science / Software Engineering / AI

Tools

TensorRT

CI/CD

AWS

Job description

## 岗位信息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 Originally posted on Himalayas