Support product requirement definition, feature analysis, and product testing.Translate customer problems and operational needs into clear engineering inputs.Work closely with engineering teams to validate product functionality and usability.
Collaborate with the sales teams in receiving enquiry, evaluating scope, preparing scope summary to be sourced both from internal and external suppliers.
Plan, coordinate and supervise mechanical tool installation activities to ensure works are executed in accordance with approved drawings, specifications, project schedule and client requirements.
Provide technical support to customers, as well as operations and sales department. Duties include conducting official plant trial mixes, monitoring of in-situ concrete performance at site, and providing technical data or specifications that is required by customers and internal departments
Create, update and maintain 2D drawings and 3D BIM models using relevant software such as AutoCAD and Autodesk Revit, according to project requirements. Read and interpret architectural, civil and structural (C&S), and mechanical, electrical and plumbing (MEP) drawings and specifications. Assist with preparing and revising construction drawings, shop drawings, coordinated models and project documentation. Incorporate design changes, mark-ups and feedback from engineers, coordinators and project teams accurately and within agreed timelines. Learn and apply project standards for BIM modelling, drawing presentation, naming conventions, model organisation and quality checks. Support model coordination by identifying drawing/model inconsistencies and escalating potential clashes or discrepancies to the relevant team. Maintain orderly files, drawing revisions and documentation in line with project procedures. Collaborate with multidisciplinary teams and participate in training, reviews and progress discussions. Follow applicable workplace, site, information-security and health-and-safety requirements
Assist in reviewing sales handover budget to project department with reference to standards in compliance with the company policies, statutory requirements and contract specifications.
Responsible for planning and execution of the projects management which includes prepare, schedule, coordinate, monitor and supervise the assigned engineering projects.
About the job We are seeking an experienced Machine Learning Engineer to join a fast-growing technology company, building and scaling machine learning capabilities across its products and platforms. This is an opportunity to work at the intersection of machine learning, software engineering, and cloud infrastructure, taking ML solutions from experimentation through to reliable, scalable production deployment. Responsibilities You will design, develop, and productionise machine learning models and services, working closely with data scientists, software engineers, and product teams to integrate ML capabilities into technology products. You will build and maintain MLOps infrastructure and automated ML pipelines covering model training, testing, deployment, monitoring, and retraining. You will establish CI/CD practices for machine learning, improve model reliability and performance, and develop scalable infrastructure to support models in production. You will also contribute to ML platform architecture, model serving, observability, and automation, ensuring machine learning systems are scalable, secure, and efficient. Requirements We are looking for an experienced Machine Learning Engineer with 6-10 years experience , strong software engineering fundamentals and hands-on experience deploying and operating machine learning models in production. Strong proficiency in Python and experience with machine learning frameworks such as PyTorch, TensorFlow, or similar technologies are essential. You should have practical MLOps experience, including model deployment, CI/CD, model monitoring, experiment tracking, containerisation, and automated training and inference pipelines. Experience with Docker, Kubernetes, cloud platforms (AWS, Azure, or GCP), and MLOps technologies such as MLflow, Kubeflow, or equivalent tools will be highly relevant. Experience building scalable APIs, model serving infrastructure, and production ML platforms would also be advantageous. To apply Interested candidates, please send your resume to Eliza Ng at en@kerryconsulting.com, quoting the job title. Due to the high volume of applications, only shortlisted candidates will be notified. L/N 16S8060R/N R1549515