Forward Deployed Engineer (FDE) - AI Infra - SF

Description

The company's Forward Deployed Engineering team works with customers to turn research results into production systems, sitting between customer delivery and core platform development.

Forward Deployed Engineers lead complex deployments of frontier models in production. You will work inside customer environments where model performance matters, delivery is urgent, and the problem is often unclear at the start.

In the AI Infra role, you will work with customer engineers, researchers and product engineers on optimization problems in semiconductors and AI infrastructure. You will write and debug code, run experiments on real workloads and hardware, and improve the tools and product used across engagements.

You will help define the problem and what success looks like, build the software needed to test an approach, and stay with the work through validation and deployment. Work may cover inference performance and chip-design optimization. Good results pass correctness and performance checks and include improvements other engagements can reuse.

You will own the delivery state across workstreams, set the standard for quality and pace, and help the company learn from execution.

The role is based in San Francisco, with a hybrid schedule of 3 days in the office per week. Relocation assistance is offered. Travel of up to 50% is required.

Responsibilities

• Own technical delivery for agreed semiconductor and AI-infrastructure workstreams, from scoping and prototypes through validation, production deployment and adoption.
• Learn how customer engineers work and what limits them, define workloads, baselines and success criteria, and make what you build part of their daily process.
• Plan and sequence delivery, flag dependencies and blockers early, and trade off scope, speed and quality as the work evolves.
• Build and debug production-quality software yourself, including harnesses, integrations and product features that apply frontier models to chip design, verification, inference and performance engineering.
• Design reproducible experiments, evaluations, graders and benchmarks that check correctness and performance and show whether gains hold in real engineering environments.
• Investigate model behavior and failure modes with researchers, contributing evaluation or training data and targeted experiments that improve the underlying capability.
• Work with product engineers to fix tooling gaps, ship useful improvements, and feed field learning into product decisions.
• Lead technical discussions and keep customer, Product and Research teams aligned. Build enough domain and product knowledge to explain capabilities, limits and results, and keep ownership, risks and next steps visible.
• Turn successful approaches into reusable software, tools and playbooks that cut effort on future engagements and help customer teams run what was built.

Requirements

• You have 5+ years of engineering or technical deployment experience, including customer-facing work.
• You have scoped and delivered complex systems in fast-moving or unclear environments.
• You write and review production-grade software and can debug unfamiliar systems across code, integrations and runtime behavior.
• You have built or deployed systems powered by LLMs or generative models and understand how model behavior shapes the product experience.
• You simplify complexity and make fast, sound decisions under pressure.
• You communicate clearly with engineers, product teams and customer stakeholders.
• You spot risks early and adjust without slowing down.
• You stay calm and use good judgment when stakes are high.
• You have a strong product sense and have helped productize work.
• You have hands-on experience with applied machine learning, model evaluation, data quality, experimentation or model-behavior analysis.
• You can turn an unclear technical problem into a clear evaluation, a credible baseline and a reproducible experiment.
• You are comfortable learning unfamiliar technical domains and working closely with researchers, product engineers and customer engineers.
• Experience in semiconductor development, data-center systems or inference engineering is helpful.

Conditions

San Francisco based, with a hybrid schedule of 3 days in the office per week.

Travel of up to 50% is required.

Relocation assistance is offered.

Background checks follow applicable law, and candidates with arrest or conviction records are considered in line with San Francisco, Los Angeles County and California fair chance rules. For unincorporated Los Angeles County roles, the duties include protecting entrusted hardware, returning it at the end of employment or assignment, keeping non-public information confidential, and accessing secure IT systems.

The company is an equal opportunity employer and does not discriminate on the basis of protected characteristics.

Benefits

• Relocation assistance.