The Engineer will lead the lifecycle management, from development to production deployment of advanced AI and autonomous applications to address key challenges in the maritime and offshore industries. This role seamlessly integrates the development of sophisticated robotics perception models with the operationalization of these solutions within an Azure Cloud environment using Agile methodologies.
You will be part of the ABS Singapore Innovation and Research Center, working within cross-functional squads to deliver iterative value. You are expected to possess a blend of software engineering rigor, cloud architecture knowledge, and practical AI expertise to ensure our solutions are scalable, secure, and production ready.
What You Will Do:
Robotics Perception& Computer Vision
- Sensor Fusion & SLAM: Develop and implement robust sensor fusion algorithms, specifically combining Camera and LiDAR data to create accurate 3D representations and enable Simultaneous Localization and Mapping (SLAM) in complex environments.
- Advanced Detection Capabilities: Lead the development of computer vision models for automated inspection, focusing on crack detection, pattern recognition, and anomaly detection on structural surfaces.
- Image Recognition: Engineer high-precision image recognition pipelines to identify key structural features and potential defects.
- Automation: Automate the interpretation of sensor data to reduce human intervention in inspection workflows.
AI Model Development& Cloud Deployment
- Model Lifecycle Management: Develop, fine-tune, and integrate AI models for operational and safety-critical use cases, specifically targeting computer vision applications.
- Cloud Architecture: Architect, deploy, and manage scalable AI solutions on Microsoft Azure, utilizing services such as Azure Machine Learning, Azure Kubernetes Service (AKS), and Azure Functions.
- Production Deployment: Transition prototype models into production-grade applications, optimizing code for latency, throughput, and cost-efficiency.
- MLOps Implementation: Design and maintain robust MLOps pipelines for model training, versioning, evaluation, and monitoring in production.
Agile Development& Collaboration
- Agile Framework: Work within an Agile/Scrum framework, participating in sprint planning, daily stand-ups, and retrospectives to ensure timely delivery of AI features.
- CI/CD Implementation: Adopt a DevOps mindset, ensuring continuous integration and continuous deployment (CI/CD) practices are applied to machine learning and robotics workflows.
- Stakeholder Collaboration: Collaborate closely with Project Managers to translate business requirements into technical specifications and provide support to ensure smooth adoption of tools
What You Will Need:
Education and Experience
- Minimum Bachelor’s degree in Computer Science, Data Science, Robotics, Engineering, or a related field. A Master’s or PhD is preferred.
- Minimum 2 years of experience in AI/ML development and deployment, preferably in a relevant field.
Knowledge, Skills, and Abilities
- Robotics & Vision: Strong grasp of sensor fusion (Camera + LiDAR), SLAM, and experience in crack or pattern detection algorithms.
- Cloud Ecosystem: Hands-on experience with the Azure ecosystem (e.g., Azure Machine Learning, Blob Storage, Azure DevOps, Azure OpenAI Service).
- Framework Proficiency: Proficiency in machine learning frameworks such as TensorFlow or PyTorch.
- Scalable Deployment: Experience with distributed systems, cloud computing, and containerization tools (e.g., Kubernetes, Docker) for scalable AI deployment.
- API Integration: Proven experience in developing and fine-tuning AI models and integrating them via APIs.
- Soft Skills: Exceptional problem-solving skills, self-motivation, and strong communication skills to work effectively with non-technical stakeholders.
