AP - 机器学习工程师
AP - Machine Learning Engineer
注意：此职位仅用于活跃人才库目的。提交申请不保证获得雇佣。您的信息将被保存在档案中，并在有合适机会时被考虑。
我们正在寻找一位专注且有条理的机器学习工程师加入D2B团队。在这个远程职位中，您将与工程和AI团队紧密合作，设计、构建并部署可生产使用的机器学习解决方案，以解决现实中的建筑挑战。
这是一个需要动手实践的工程职位，适合喜欢将ML模型从概念阶段推进到生产环境，并在协作式、以远程优先的环境中工作的人员。
主要职责：
- 设计、开发并部署以计算机视觉应用为重点的生产级机器学习模型。
- 构建能够从视觉数据中识别、跟踪和分析建筑进度的AI功能。
- 使用大语言模型（LLMs）、多模态AI模型和生成式AI技术进行研究、原型设计和实现。
- 评估何时使用商业基础模型还是开发定制的机器学习解决方案。
- 设计、构建和维护覆盖数据收集、标注、训练、评估、部署和监控的可扩展ML流水线。
- 获取、清洗、整理并准备高质量的数据集用于模型训练。
- 开发和维护MLOps基础设施，包括模型版本控制、CI/CD流水线、部署自动化和监控。
- 与软件工程师、产品经理和AI专家合作，将机器学习功能集成到生产应用程序中。
- 优化模型准确性、推理性能、可扩展性和可靠性。
- 跟踪最新的机器学习技术、AI框架和行业最佳实践。
要求
- 计算机科学、软件工程、人工智能或相关专业的学士学位。
- 3年以上作为机器学习工程师或AI工程师的商业经验。
- 有构建和部署生产级机器学习系统的实际经验。
- 在开发计算机视觉模型方面有丰富经验。
- 有端到端MLOps经验，包括：
- 数据收集和标注
- 模型训练和评估
- 流水线开发
- CI/CD自动化
- 模型版本控制
- 监控和优化
- 有使用大语言模型（LLMs）、多模态AI模型和生成式AI技术的经验。
- 熟练掌握Python。
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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