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Liquid AI

Provides generative, edge-capable foundation models

Member of Go-to-Market Staff

Sales Development RepresentativeConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • Four to six years of go-to-market experience in B2B software, developer tools, infrastructure, or a similarly technical product category, including some experience at an early-stage company.
  • Evidence of varied go-to-market experience, such as holding multiple types of go-to-market roles or transitioning from consulting into a go-to-market role.
  • Experience being directly accountable for revenue through pipeline generation, quota-carrying roles, or strategic business development that drove commercial results.
  • Experience prospecting or selling to technical personas such as engineers, data scientists, chief technology officers, heads of artificial intelligence or machine learning, or technical founders.
  • Fluency with modern go-to-market tooling, including an example of a workflow or automation built independently.
  • Strong written communication skills and the ability to craft relevant, specific materials.
  • Ability to persist in outbound work through iteration, gathering signals, and sustained effort.
  • Ability to learn from calls, response patterns, objections, and team feedback.
  • Commercial judgment, including distinguishing activity from progress and prioritizing pipeline quality.

Responsibilities

  • Build qualified pipeline across target accounts through cold calls, tailored email outreach, LinkedIn, and creative prospecting.
  • Identify and engage technical and business stakeholders, including engineering leaders, artificial intelligence and machine learning teams, product leaders, and executives.
  • Conduct early-stage qualification conversations to assess fit and determine where to focus effort.
  • Partner with sales and partnerships teams on account strategy, messaging, sequencing, and handoff quality.
  • Support active deal cycles when useful, particularly to capture learnings that improve pipeline generation and qualification.
  • Surface market insights from customer interactions, including objections, effective messaging, competitor patterns, use-case trends, and signals that should shape positioning.
  • Define qualification criteria and handoff standards to maintain pipeline quality while the company scales.
  • Build the outbound playbook, including target account strategy, messaging frameworks, channel mix, sequencing, and operating cadence.
  • Maintain rigorous customer relationship management discipline and use the data to support rapid learning.
  • Generate a meaningful share of qualified pipeline and build automated systems that create opportunities without constant manual effort.
  • Close sourced or carried revenue and develop strong, expanding customer relationships.
  • Gather customer feedback that informs leadership decisions, new initiatives, product development, and positioning.
  • Scope growth campaigns, coordinate execution with marketing, and produce measurable results.
  • Document, automate, and improve the repeatability of the go-to-market playbook.

Desired Qualifications

  • Experience in a Series A-C or another early-stage environment.
  • Familiarity with artificial intelligence and machine learning concepts or experience selling to technical infrastructure buyers.
  • Experience using qualification frameworks such as MEDDIC, BANT, or similar.

About the Company

Liquid AI

Provides generative, edge-capable foundation models

Liquid AI builds and deploys foundation models based on liquid neural networks, focusing on efficient, on-device AI. It develops Liquid Foundation Models (LFMs), a family of generative AI models designed to be smaller and more computation-efficient than typical large language models, enabling deployment on edge devices with lower latency, better privacy, and reduced infrastructure costs. The approach includes end-to-end AI expertise and customizable architectures for enterprises that require real-time performance and private processing. Compared to traditional AI providers, Liquid AI emphasizes edge-ready, adaptable models that run efficiently on constrained hardware, and it targets enterprise-grade, private, reliable AI solutions. The company’s goal is to enable real-time, on-device AI at scale for businesses by offering compact, capable foundation models and the tools to customize them for specific applications.

Company size
51-200
Company stage
Series A
Total funding
$287.5M
Headquarters
Brookline, MA
Founded
2023

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