We are hiring an AI Engineer to join a global automation engineering team within a manufacturing environment. This role focuses on designing, developing, and deploying AI/ML/DL solutions to improve quality, manufacturing efficiency, and business performance across multiple sites. You will work at the intersection of data science, software engineering, automation, and manufacturing processes, partnering with cross-functional stakeholders globally.
Responsibilities
- Design and build an AI-enabled UI platform for data labelling/annotation, model training, validation, and deployment across multiple manufacturing sites.
- Develop and deploy AI/ML/DL solutions for automation and manufacturing use cases (e.g., computer vision, predictive analytics).
- Create models using MES and related manufacturing data for process optimisation and predictive insights.
- Support testing and rollout of an OCR solution for serial/part number extraction.
- Develop and enhance cycle time prediction models in collaboration with enterprise systems and data engineering teams.
- Support and improve an internal AI assistant using LLM frameworks to provide manufacturing insights and user support.
- Build and integrate operations dashboards, including modules for planned production time and ideal cycle time inputs.
- Develop AI-enabled tools to improve quoting speed, accuracy, and consistency.
- Lead requirement discovery with stakeholders and manage delivery across multiple parallel workstreams.
- Communicate technical outcomes clearly to both technical and non-technical stakeholders.
Requirements
- Bachelor's/Master's in Computer Science, AI, Software Engineering, or related discipline.
- 3 + years experience delivering AI/ML solutions, preferably in advanced manufacturing or industrial environments.
- hands-on experience in deep learning, computer vision, predictive modelling, and production deployment.
- Proficiency in Python and deep learning frameworks (TensorFlow and/or PyTorch).
- Experience with OpenCV and building interactive tools/APIs (e.g., Streamlit, FastAPI, or similar).
- Experience working with MES/SAP (or equivalent) manufacturing data and KPIs (e.g., OEE, cycle time, yield).
- Familiarity with MLOps tools (e.g., MLflow, Kubeflow, Airflow) and cloud environments (AWS/Azure/GCP).
- Understanding of industrial integration concepts (e.g., edge devices, PLCs, automation systems).
- Ability to lead cross-functional initiatives, manage multiple priorities, and communicate effectively in a global environment.
- Preferred: experience deploying OCR and LLM-based applications in production, and exposure to predictive maintenance or equipment anomaly detection.
EA: 14S7084 | Registration No: R1981018
