AI Field Engineer, Singapore
Fireworks AI18 days ago
Responsibilities
- Build end-to-end POCs and MVPs with customer engineering teams inside their codebases and infrastructure.
- Architect and size inference foundations for GenAI products so they can scale without infrastructure bottlenecks.
- Run load tests, establish latency, throughput, and cost baselines, and tune deployments against realistic traffic.
- Deploy and validate model families using inference frameworks, optimizing model shapes, quantization configurations, and serving patterns.
- Advise customers on model selection, fine-tuning strategies including SFT, DPO, and RFT, and evaluation methodology.
- Build fine-tuning pipelines and evaluation frameworks that measure production-quality outcomes.
- Lead discovery conversations, align stakeholders, and own the technical relationship from initial engagement through production deployment.
- Work on-site with customers to build trust, momentum, and solutions within their teams.
- Translate recurring customer pain points, deployment patterns, failure modes, and feature gaps into product proposals and roadmap feedback.
- Codify repeatable deployment patterns in internal tooling, documentation, and the platform.
Requirements
- At least 5 years of hands-on experience in customer-facing technical roles such as Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder.
- Demonstrated ability to build and ship production software within customer environments rather than only providing advice.
- Strong Python skills and experience reading, writing, and debugging production code.
- Familiarity with Kubernetes and infrastructure engineering.
- Working knowledge of LLM inference trade-offs, model serving, and fine-tuning workflows, with SFT required and DPO/RFT beneficial.
- Experience with AWS, Azure, or GCP cloud infrastructure and deploying models on GPU infrastructure.
- Strong communication skills for discovery calls, VP presentations, and technical debugging with ML engineers.
- Preferred: 10+ years in technical field or engineering roles.
- Preferred: experience with vLLM, SGLang, or TensorRT-LLM and tuning inference deployments for real workloads.
- Preferred: experience serving as a technical authority within customer infrastructure and shipping production code there.
- Preferred: experience taking GenAI POCs to production scale.
- Preferred: experience with Azure AI Foundry, AWS Bedrock, AWS SageMaker, or GCP Vertex.
- Preferred: experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains.
Benefits
- The role includes on-site customer work and embedding with customer teams in person.
- The company emphasizes ownership, direct impact, collaboration with experienced engineers and AI researchers, and work on advanced AI infrastructure.
- Fireworks is an equal-opportunity employer committed to an inclusive workplace.