Forward Deployed Engineer
South Korean AI semiconductor and infrastructure company building inference accelerators, servers, racks, and software for production-scale AI deployment.
Funding history
Investors
About Rebellions
Rebellions develops purpose-built AI inference hardware and an accompanying software stack. Its current offerings include the Rebel100 accelerator and deployable RebelServer, RebelRack, and RebelPOD systems, designed for energy-efficient data-center inference.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead technical customer engagements from initial discussions through proof-of-value design and execution. You will deliver demos and presentations, prototype deployment architectures, evaluate inference performance, troubleshoot deployments, create integration documentation, and relay customer feedback to engineering teams.
Requirements
- Bachelor’s degree in Computer Science Electrical Engineering or a related technical field
- At least three years of experience deploying AI or ML systems engaging customers or working in solutions engineering
- Experience deploying Kubernetes-based AI inference stacks
- Familiarity with distributed LLM inference orchestration
- Working knowledge of Python and PyTorch
- Presentation storytelling communication and collaboration skills
- English fluency
- Singapore citizenship
Responsibilities
- Lead technical customer engagements through proof-of-value design and execution
- Build and deliver product demos technical presentations and benchmarking content
- Design and prototype customer deployment reference architectures
- Evaluate inference performance and optimize serving and routing strategies
- Guide customer technical teams through architecture deployment and troubleshooting
- Create technical documentation integration guides and best practices
- Relay customer feedback to software and hardware engineering teams
Hiring Process
Application review > First online interview > Second interview with technical exercise and culture-fit session > Management interview > Final on-site interview