Material

Solutions Engineer

🇺🇸 San Francisco, United States On-site IT Senior Posted May 18, 2026
Location San Francisco, United States
Workplace On-site
Seniority Senior
Category IT
IT Category Solutions / Architecture
Language English
Posted May 18, 2026
Last verified June 10, 2026
JobGrid context

Role summary by JobGrid

Solutions Engineer at Material: San Francisco, United States; On-site; Senior; IT; Solutions / Architecture. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.

  • Location and workplace: San Francisco, United States, On-site
  • Role classification: IT, Solutions / Architecture, Senior
  • Source freshness: checked by JobGrid on 2026-06-10.
  • Application path: candidates continue to the employer application page with non-personal referral tags.

About the role

Own the technical strategy, execution, and delivery of customer engagements from pre-sales discovery through deployment. You'll partner with Sales to architect AI infrastructure solutions for Frontier labs, startups, and enterprise ML teams, translating customer requirements into production workloads.

What you'll do

  • Own customer POCs: scope, success metrics, architecture, timeline, and production handoff

  • Deliver technical demonstrations tailored for engineering leaders and executive audiences

  • Architect solutions across training, fine-tuning, and inference

  • Map technical requirements to business outcomes

  • Build deep relationships with customer stakeholders

  • Build reusable demos, reference architectures, and playbooks

  • Partner with product and engineering to translate customer needs into roadmap priorities

What you'll need

  • BS in CS, EE, or related field, or equivalent experience

  • 5+ years in a customer-facing technical role: solutions architect, forward deployed engineer, or product management

  • Proficiency in one or more programming languages: Rust, Go, or Python

  • Strong understanding of AI/ML infrastructure: GPUs, distributed training, inference serving

  • Experience with Kubernetes, Docker, and Slurm

  • Strong understanding of training, fine-tuning, and inference

  • Proven ability to run technical evaluations and influence outcomes in complex sales cycles

  • Excellent communication skills: can explain infrastructure and model behavior clearly to both technical and executive audiences

  • High ownership and comfort with ambiguity, with strong prioritization across multiple deals and customer threads

What we offer

  • Top-tier compensation structured to recognize and retain the best talent

  • Meaningful equity

  • Comprehensive medical, dental, vision, life, and disability insurance

  • Parental leave for all new parents, including adoptive and surrogate journeys

  • Flexible PTO

  • Paid Holidays

  • Relocation support

 

Equal Employment Opportunity

We're an Equal Opportunity Employer and do not discriminate on the basis of any protected status under applicable law.