Overview
Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware, a position that took years to build.
About the Role
We're looking for a Go-to-Market Engineer to build the commercial operating system for Inferact from the ground up. The GTM organization is early enough that core infrastructure such as CRM structure, account intelligence, standardized workflows, and repeatable operating processes are still being defined. You'll partner closely with commercial leadership to turn fragmented information into systems that make the team faster, more focused, and more effective.
This is primarily a hands-on GTM engineering role, combining technical building with a secondary RevOps remit. Early projects will include creating a clean commercial source of truth, helping define the sales process, mining Inferact's unique ecosystem and community data to identify high-value prospects and warm paths, and building the workflows and automation that support targeted selling. As the ICP becomes clearer, you'll help evolve the system toward scalable prospecting, reporting, and commercial execution without adding unnecessary process. As the sales team grows, you'll also help define rep onboarding and training and support sales compensation planning, with those broader RevOps needs expected from 2027 at the earliest.
Skills and Qualifications
Minimum qualifications:
Experience building or operating go-to-market systems, revenue operations, sales operations, or GTM engineering workflows in a startup or high-growth technology environment.
Hands-on experience implementing and structuring a CRM, including account and opportunity data models, pipeline stages, required fields, routing, process hygiene, and reporting.
Strong ability to work with data, APIs, integrations, enrichment sources, automation tools, and lightweight scripting to turn fragmented commercial information into usable workflows.
Understanding of how an early-stage sales organization operates, including ICP definition, prospect research, pipeline management, handoffs, follow-up, and the difference between useful process and unnecessary process.
Ability to take a blank-sheet problem, identify the highest-leverage operating system to build, and ship it without waiting for detailed requirements.
Strong communication and collaboration skills with the ability to work directly with commercial leadership, founders, product, engineering, and external implementation partners.
Ability to translate commercial needs into clear system and data requirements and communicate tradeoffs to both technical and non-technical stakeholders.
Preferred qualifications:
Experience building 0-to-1 GTM infrastructure before a company had a mature CRM, documented ICP, or standardized sales process.
Experience mining proprietary or community data sources to identify high-value accounts, warm paths, customer signals, or technically relevant prospects.
Experience with AI-native or modern GTM workflows, including research automation, enrichment, account intelligence, workflow orchestration, and highly personalized outbound support.
Experience supporting developer tools, AI infrastructure, open-source software, cloud platforms, or another highly technical B2B product.
Comfort combining hands-on GTM engineering with RevOps judgment; experience defining rep onboarding and training or supporting sales compensation plans is a plus for the role's longer-term scope.
Bonus points if you have:
Built a CRM and commercial operating cadence from scratch for an early-stage startup.
Created account research, enrichment, warm-intro mapping, or prospect prioritization systems that materially improved seller focus.
Automated repetitive GTM workflows while preserving high-quality human judgment for strategic accounts.
Worked with open-source communities or product-usage data as a source of commercial intelligence.
Built internal GTM tools, dashboards, agents, or data pipelines that became core infrastructure for a commercial team.
Logistics
Location: This role is based in San Francisco, California and is on-site.
Compensation: Compensation will be determined based on background, skills, and experience. Offers include equity.
Visa sponsorship: We sponsor visas on a case-by-case basis.
Benefits: Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.
Job details are sourced from the employer's original posting.
Open job postingAbout the company
Inferact is a company focused on optimizing AMD GPU workloads, particularly for machine learning kernels and inference paths. They specialize in deep understanding of GPU execution, memory behavior, and toolchains to enhance performance.