Graduate Hiring - Golang Engineer (RWA)
- Mentorship and Networking with Industry Leaders!
28 days
400+ Graduate Software Engineer Jobs - October 2026 - High Salaries - Page 15
Showing 444 jobs results for
"graduate software engineer"
- Design and implement workload scheduling across multiple data centers, regions, and cloud environments, ensuring balanced resource utilization and efficient placement of both online services and offline batch jobs.
29 days
- Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
28 days
- Based on Southeast Asia business scenarios and Agent applications, participate in designing AI business implementation scenarios to help improve business efficiency and solve business pain points.
28 days
Software Developer (Open to fresh entry level)
Today
- AI scenarios: Participate in the application of AI in client-side development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
1 day
AI Engineering Graduate Talent Trainee
- Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
4 days
AI Engineering Graduate Talent Trainee
- Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
4 days
- AI scenarios: Participate in the application of AI in client-side development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
4 days
- Participate in design reviews and code reviews;
6 days
- Integrate AI Agents into daily R&D workflows and explore their applications in scenarios such as coding assistance, intelligent debugging, automated testing, issue troubleshooting, and business process automation.
6 days
- AI scenarios: Participate in the application of AI in client-side development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
22 days
- Track quality performance, identify root causes, and drive improvements in production processes and execution.
5 days
Software Engineer in Machine Learning Infra, Recommendation Architecture (ByteDance Singapore)
- Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.
11 days
Software Engineer in Machine Learning Infra - Recommendation Architecture (ByteDance Singapore)
- Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.
11 days
- AI scenarios: Participate in the application of AI in client-side development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
27 days
- AI scenarios: Participate in the application of AI in client-side development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
25 days
AI Engineering Graduate Talent Trainee
- Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
26 days
AI Engineering Graduate Talent Trainee
- Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
26 days
- AI scenarios: Participate in the application of AI in client-side development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
26 days
- Integrate AI Agents into daily R&D workflows and explore their applications in scenarios such as coding assistance, intelligent debugging, automated testing, issue troubleshooting, and business process automation.
27 days
- Participate in design reviews and code reviews;
28 days
- Troubleshoot, debug, and upgrade existing systems.
30+ days