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Solutions Engineer

Material Depot - San Francisco, CA | Hybrid | Remote

Posted Jun 10, 2026

Benefits

Parental leave
Not verified
Non-birth-parent leave
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Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Verification
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Salary
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401(k) match
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Market context

U.S. role benchmark (BLS OEWS)
$57,704 U.S. median for this role
Projected growth (BLS Employment Projections)
+0.9% - Slower

Matched to SOC 41-2031 - Sales aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Sales From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026
Work mode
Hybrid From the posting source checked Jun 20, 2026
In-office days
2 days From the posting source checked Jun 20, 2026

Schedule

Shift type
Not verified
Weekend work
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Company

Equity
Offered From the posting source checked Jun 20, 2026

Application

Cover letter
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Assessment
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Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Solutions Engineer San Francisco, CA | Hybrid | Remote 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

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