Forward Deployed Engineer (FDE) - AI Infra - SF
$185k - $300k • San Francisco • FullTime
Posted 11h ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Infrastructure Engineer
About the job
OpenAI's Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems, operating at the intersection of customer delivery and core platform development. As a Forward Deployed Engineer for AI Infra, you will lead complex deployments of frontier models in production, embedding with customers where model performance and urgent delivery are critical. You will work directly with customer engineers, researchers, and product engineers on optimization problems across semiconductors and AI infrastructure, writing and debugging software, running experiments, and improving tools. Your role involves defining problems, structuring delivery, and shipping fast, with a focus on inference performance and chip-design optimization, ultimately contributing improvements to OpenAI's platform.
Responsibilities
- Own technical delivery for semiconductor and AI-infrastructure workstreams, from scoping to production deployment.
- Collaborate with customer engineers to understand workflows, define workloads, and integrate solutions.
- Scope and sequence delivery, identify dependencies, and manage trade-offs between scope, speed, and quality.
- Build and debug production-quality software for applying frontier models to chip design, verification, inference, and performance engineering.
- Design and execute reproducible experiments, evaluations, and benchmarks to validate correctness and performance.
- Investigate model behavior and failure modes, contributing data and experiments to improve underlying capabilities.
- Contribute to core product development by resolving tooling gaps and incorporating field learnings.
- Lead technical discussions and maintain alignment across customer, Product, and Research teams.
- Develop reusable software, tools, and playbooks to streamline future engagements.
Requirements
- 5+ years of engineering or technical deployment experience, including customer-facing work.
- Experience scoping and delivering complex systems in fast-moving or ambiguous environments.
- Proficiency in writing and reviewing production-grade software, and debugging unfamiliar systems.
- Experience building or deploying systems powered by LLMs or generative models.
- Ability to simplify complexity and make sound decisions under pressure.
- Clear communication skills with engineers, product teams, and customer stakeholders.
- Ability to spot risks early and adjust without slowing down.
- Strong product sense and experience with productizing efforts.
- Hands-on experience with applied machine learning, model evaluation, data quality, experimentation, or model-behavior analysis.
- Ability to translate ambiguous technical problems into clear evaluations, credible baselines, and reproducible experiments.
- Comfort learning unfamiliar technical domains and working closely with researchers and engineers.
- Experience in semiconductor development, data-center systems, or inference engineering is helpful.