jobapplierForward Deployed Engineer, BytePlus - Singapore
- Singapore
- Mid Level
- Posted
Skills
Required
- network
- content generation models
- application development
- AI coding tools
- public cloud
- cloud architectures
- storage
- Kubernetes
- databases
- deploying landing zones
- CI/CD pipelines
Preferred
- evaluation engineering
- large language and content generation models
- AI Cloud
- GPU
- training/inference/RL platforms
- solution feasibility
About ByteDance
BytePlus is one of the newer Business Units formed to serve global enterprise customers with our leading technology solutions. As part of the BytePlus Team, you help enterprise customers build what's next for their business. Leveraging ByteDance's cutting-edge intelligent technologies, we are devoted to developing innovative products and solutions to shape the future. We empower our clients to focus on what truly matters. Centering on inspiring innovativeness and excellence, we create life-changing solutions that impact lives around the world. You can help us to achieve our mission.
Responsibilities
- Collaborate closely with key accounts in the capacity of an AI consultant to explore opportunities in AI transformation.
- Develop a customer AI transformation roadmap, taking into account value proposition, solution feasibility, and integration with existing systems and processes.
- Construct a demonstration for the proposed solution within the customer's business context and system environment.
- Generate documentation for jointly-created solutions, value propositions, technical architecture, and customer feedback.
- Ascertain common customer requirements or market needs and construct prototypes for industry solution portfolios.
Requirements
- Possesses an engineering background, extensive experience in application development, and proficiency in utilizing AI coding tools.
- Demonstrates in-depth knowledge and practical hands-on experience in using public cloud products and constructing cloud architectures (including compute, storage, network, Kubernetes, databases, and security).
- Has practical hands-on experience in deploying landing zones and setting up CI/CD pipelines.
- Is familiar with common large language models and content generation models, capable of comprehensively analyzing the advantages and disadvantages of these models and their typical use cases.
- Has hands-on experience in building AI agents, covering prompt optimization, knowledge/memory base management, tool utilization, and observability.
Preferred
- Experience in the evaluation engineering of large language and content generation models.
- A solid understanding of AI Cloud, including GPU, network, and training/inference/RL platforms.