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The Machine Learning Engineer will design, develop, and deploy production-grade AI solutions with a focus on geospatial applications. The role involves architecting scalable ML systems, implementing MLOps best practices, and mentoring team members using Python, PyTorch, and containerization tools.
The AI Engineer will lead the design and deployment of production-grade machine learning solutions, specifically focusing on geospatial applications. The role involves architecting scalable systems, implementing MLOps practices, and mentoring team members using technologies like Python, PyTorch, and Docker.
The Project Manager will lead complex AI, GenAI, and data platform initiatives within the financial services sector. The role involves managing project lifecycles, budgets, and multi-stakeholder coordination using Agile methodologies and JIRA.
The Product Manager will lead the development of AI-powered education products by managing roadmaps, collaborating with engineering and AI teams, and translating user needs into actionable product requirements. This role requires experience in digital product management and a strong understanding of the product development lifecycle.
The AI Architect will lead the design and implementation of enterprise-scale AI and Generative AI solutions, serving as the technical authority for AI initiatives. The role involves defining architecture roadmaps, establishing governance standards, and mentoring teams using technologies like LLMs, RAG, cloud platforms, and MLOps.
The AI Engineer will design, develop, and deploy AI-powered enterprise solutions using machine learning, Generative AI, LLMs, and RAG architectures. The role involves building scalable AI applications, optimizing models, and integrating them into cloud-based microservices architectures.
The Lead AI Research Engineer will design and implement evaluation frameworks for LLM and agent systems to ensure reliability and performance. This role involves conducting empirical research, building evaluation infrastructure, and guiding technical decisions for AI-native research products.
The Research Fellow will develop and deploy AI algorithms for digital health projects at the Asian Centre for Health Behavioural Insights & Interventions. The role involves managing research operations, collaborating with clinical teams, and publishing findings in high-impact journals.
The Lead Data Scientist will design and maintain predictive models to identify customer readiness for AI product adoption. The role involves collaborating with marketing and product teams to operationalize these models and drive data-informed growth strategies.
This 12-month graduate management associate programme at DBS offers rotations in technology, AI, and data science tracks to develop future leaders through hands-on projects and structured training. Participants will work on software development, cybersecurity, cloud infrastructure, or advanced AI/ML solutions including GenAI and agentic frameworks.
The Deep Learning Solution Architect will drive the development and optimization of reinforcement learning and post-training frameworks for LLMs and multimodal models, providing technical guidance to customers on NVIDIA's AI platforms.
NVIDIA is seeking a Senior Solution Architect to collaborate with OEM partners on the design and deployment of Arm-based data center CPU platforms. The role involves performance tuning, workload migration from x86 to Arm, and providing technical leadership to ensure the scalability and reliability of next-generation enterprise and AI server infrastructure.
The Cybersecurity AI Solutions Engineer will design and deploy AI security solutions within virtualized digital twin environments and fine-tune LLMs like NVIDIA Nemotron for threat detection. The role involves bridging AI development, cybersecurity architecture, and DevOps practices to secure NVIDIA networking products.
This RDSS internship role involves developing system software diagnostics and validation tools for NVIDIA's next-generation GPU products. The intern will work on stress testing, automation, and failure analysis to support manufacturing and datacenter workflows.
The Senior Business Intelligence Analyst will lead the architectural design and development of end-to-end BI solutions, collaborating with global teams to deliver data-driven insights. The role requires extensive experience in data modeling, warehousing, and visualization using tools like SQL, Tableau, Power BI, and cloud platforms like Snowflake or Databricks.
The Senior AI Engineer will design and deploy cloud-based data pipelines, machine learning models, and full-stack applications to support manufacturing operations. The role involves leveraging GCP, Vertex AI, and modern MLOps practices to build scalable AI solutions and GenAI initiatives.
The Applied AI Senior Consultant will lead the design and delivery of AI-powered solutions for healthcare payer organizations, bridging the gap between operational challenges and technical implementation. The role involves advising executives, managing client engagements, and utilizing technologies like LLMs, RAG, and agentic AI to improve workflows such as claims processing and utilization manage
The Forward Deployed Engineer will build and deploy AI-powered products for financial clients, working across the full stack including Python, C#, React, and Azure. This role involves embedding with investment teams to translate business needs into scalable, production-grade AI solutions.
The AI Engineer will design, build, and deploy enterprise AI solutions, including copilots and agents, using Microsoft Copilot Studio, Microsoft Foundry, and Azure AI services. The role involves working directly with customers to implement RAG architectures, custom integrations, and secure AI workflows.
The Design Lead will conduct user discovery, design workflows, and build prototypes for client AI projects and internal products using AI-assisted tools. This hands-on role requires working directly with engineers and stakeholders to ensure designs are evidence-based and implementation-ready.
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