AI Field Engineer, Singapore
Singapore • FullTime
Posted 1mo ago
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Fireworks is seeking an AI Field Engineer to join their team in Singapore. This role is at the forefront of technical engagement, embedding with key customers and partners to transform complex AI challenges into production-ready systems. You will operate at the nexus of engineering, product development, and customer delivery, actively building proofs-of-concept (POCs), minimum viable products (MVPs), and production integrations. Simultaneously, you will engage in high-level discussions regarding architecture, strategy, and business impact. The position requires a blend of hands-on coding, performance benchmarking, debugging, and deployment architecture, alongside leading customer discovery, aligning stakeholders, and translating customer needs into product enhancements.
Responsibilities
- Build end-to-end POCs and MVPs with customer engineering teams, working within their existing codebases, infrastructure, and constraints.
- Architect inference foundations for customers whose core products are GenAI-based, and size deployments for scalability without infrastructure bottlenecks.
- Conduct load tests and establish latency, throughput, and cost baselines against realistic customer traffic, tuning deployments to meet targets.
- Deploy and validate new model families on inference frameworks like vLLM and SGLang, optimizing configurations and serving patterns.
- Advise customers on model selection, fine-tuning strategies (SFT, DPO, RFT), and evaluation methodologies.
- Build and execute fine-tuning pipelines with customers, balancing model families, compute costs, and quality objectives.
- Design and implement evaluation frameworks to measure production-quality metrics.
- Help customers integrate frontier model capabilities into their core offerings to create a competitive advantage.
- Lead discovery conversations to understand customer pain points, constraints, and success criteria before proposing solutions.
- Manage the technical relationship from initial engagement through production deployment, building trust with both ML engineers and VPs.
- Spend time on-site with customers to build trust and momentum by embedding with their teams.
- Identify recurring customer pain points and translate them into actionable product proposals for engineering and product teams.
- Codify repeatable deployment patterns for internal tooling, documentation, and the platform.
- Provide specific and urgent feedback on customer signals to the product roadmap.
Requirements
- 5+ years in a hands-on, customer-facing technical role (e.g., Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field experience, or technical founder).
- Proven ability to build production software with customers, having shipped code running in external production environments.
- Strong Python skills, with proficiency in reading, writing, and debugging production code.
- Familiarity with Kubernetes and infrastructure engineering.
- Working knowledge of the LLM stack, including inference trade-offs, model serving, and fine-tuning workflows (SFT minimum; DPO/RFT a plus).
- Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure.
- Exceptional communication skills, capable of leading discovery calls, presenting to VPs, and debugging technical issues.