---
title: 'Strategic Business Development, Startups Lead at Liquid AI'
canonical: 'https://feeny.ai/job/strategic-business-development-startups-lead-liquid-ai-san-francisco-pg3krfkentsx'
type: 'job'
last_seen: '2026-11-10'
---

# Strategic Business Development, Startups Lead at Liquid AI

- **Company:** Liquid AI
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-11-06
- **Last confirmed live:** 2026-11-10
- **Apply:** https://jobs.ashbyhq.com/liquid-ai/fbccf92f-2073-46a6-b9ee-1c285ffbe676

## Job description

## About Liquid AI

Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.

The Opportunity As the first person on our business team focused entirely on startups, you’ll turn growing interest from founders and technical teams into a business. You’ll win and grow startup customers, design the program and commercial offers to serve them at scale, and bring their needs back to the engineers building the product. Working closely with engineering, our ML teams, and marketing, you’ll have the autonomy to shape how we serve startups.

## What We're Looking For

We need someone who:

- Learns fast: You get up to speed on a new product, customer, or market quickly, and you rarely need something explained twice. We ship frequently; you learn each release from the docs and the engineers who built it, then explain it accurately to customers.
- Moves from idea to live: You turn an idea for an offer or a program into something customers can use, document just enough to make it repeatable, and refine it as results come in, rather than waiting on a finished strategy document.
- Keeps founder pace: You work the way startups do: you respond quickly on whatever channel a founder prefers, move from first conversation to signed deal in days or weeks, and run deals yourself rather than through a team.

The Work

- Own startup revenue: qualify and close inbound demand, grow accounts as customers move into production, and take new offerings to startups as our platform expands.
- Build outbound alongside a strong inbound flow, using hackathons, developer communities, and VC and accelerator relationships to find the startups that should be building on Liquid.
- Design and run our startup program: who qualifies, what they get (credits, community, access to our team), and how they move to paid usage, with economics that work for Liquid.
- Create commercial offers that make deals repeatable, such as committed-spend agreements backed by dedicated capacity, and sell them.
- Turn customer feedback into product improvements: bring friction in billing, limits, documentation, and missing features to engineering as clear, prioritized requests, and follow them through to release.

## Experience & Capabilities

What you'll need:

- Sharp commercial judgment, the capability that matters most in this role: you can design an offer or deal structure (credits, usage-based pricing, committed spend) that works for the customer and for Liquid, and walk through its economics.
- A track record of selling directly to startups: you have closed deals with founders and technical teams and know how they evaluate, buy, and scale.
- Experience selling a technical platform, such as cloud, data, or AI infrastructure, that customers build on rather than a finished application.
- Enough technical fluency to earn engineers' respect: you can discuss models, APIs, latency, and cost, ask useful questions, and keep up in technical conversations.

Helpful, not required:

- Experience at an early-stage startup.
- Experience building a startup, developer, or partner program, or relationships with the VCs, accelerators, and founder communities that feed one.
- A technical background, such as engineering experience or a customer-facing technical role.

What Success Looks Like (Year One)

- Startup revenue has grown many times over.
- Startups have a repeatable path from first credits to committed contracts: a program and commercial offers that close again and again without being reinvented for each deal.

## What We Offer

- Write the playbook: You'll decide how Liquid wins and serves startups, from the program to the deals, and shape the product directly with the engineers who build it.
- Compensation & Equity: Competitive base salary plus equity, so you share in what we build. Final offers reflect skills, experience, and location.
- Time Off: Unlimited PTO, plus company-wide Refill Days, long weekends when the whole company rests together.
- Health & Wellbeing: Comprehensive health coverage, with details varying by location.
- Paid Leave: Paid leave for pregnancy, parenting, medical needs, and caring for family.

## About Liquid AI

## Company Overview
- **One-liner**: Liquid AI builds efficiency-first, general-purpose foundation models designed to run on-device and at the edge, delivering state-of-the-art performance with minimal compute.
- **Entity Type**: Private (Series A)
- **Headquarters**: Cambridge, Massachusetts, United States
- **Founded**: 2023
- **Founders**: Ramin Hasani (CEO), Mathias Lechner (CTO), Alexander Amini (CSO), Daniela Rus

## Core Business
- **Primary Industry**: Artificial Intelligence / Foundation Models
- **Target Customers**: B2B; Enterprise (e.g., automotive, finance, defense, e-commerce, biotech); developers building on-device or edge AI applications.
- **Mission**: To build efficient general-purpose AI at every scale — highly capable, compute-optimized, and ready to run on any device.

## Products & Services
- **Liquid Foundation Models (LFMs)**: A new generation of generative AI models optimized for on-device and edge deployment. They achieve state-of-the-art performance with a smaller memory footprint and more efficient inference than traditional transformers. Models range from 230M to 24B parameters, including specialized variants for vision (VL), multilingual search (Retrievers), and mixture-of-experts (MoE).
- **Liquid Edge AI Platform (LEAP)**: A full-stack SDK for fine-tuning, baking, and deploying LFMs to production. Supports runtimes like llama.cpp, MLX, ONNX, CoreML, SGLang, and vLLM, enabling rapid customization and deployment.
- **Research & White-Box Models**: The company publishes its research on liquid neural networks and state-space models in the open, emphasizing explainable, traceable AI over black-box approaches.

## Market Standing
- **Valuation**: Not publicly disclosed.
- **Key Metric**:
  - **Total Funding**: $293.2M
  - **Annual Revenue**: $34.5K (early-stage; likely pre-revenue or nominal)
- **Notable Investors/Partners**: AMD Ventures (led Series A), OSS Capital, Stephen Pagliuca; partners include Mercedes-Benz (in-car intelligence), Insilico Medicine (drug discovery), and hardware/infrastructure providers.
- **Growth Signals**:
  - Headcount of ~91 employees (as of mid-2026), with 8% monthly growth.
  - Active job postings: 18 (quarterly growth of +63.6%).
  - Rapid international expansion: operates in 12 countries including Japan, Germany, Spain, and France.
  - Recent product launch: LFM2.5 series (June 2026) — next-gen on-device models.
  - Strong talent pipeline: hires from MIT CSAIL, Stanford, Amazon, Meta, and Citadel.

## Competitive Advantages
- **Efficiency-First Architecture**: LFMs are designed from the ground up for compute- and cost-optimized inference, enabling deployment on phones, laptops, cars, and other edge devices where traditional LLMs are too large or slow.
- **White-Box Explainability**: The company prioritizes transparent, inspectable models over black-box systems — a key differentiator for regulated industries.
- **Rapid Customization**: The LEAP SDK allows clients to fine-tune and deploy specialized models in minutes, not weeks.
- **Strong Academic Roots**: Spun out of MIT CSAIL with a founding team of world-class researchers in liquid neural networks and state-space models.

## Strategic Focus
- **On-Device & Edge AI**: Primary growth vector is bringing advanced intelligence to processors outside data centers (automotive, mobile, IoT, defense).
- **Enterprise Partnerships**: Deepening collaborations with Mercedes-Benz (automotive) and Insilico Medicine (biotech) to embed LFMs into real-world products.
- **International Expansion**: Building out teams in Japan, Europe, and beyond to capture global demand for localized, on-device AI.
- **Model Line Expansion**: Continuously releasing new model sizes and modalities (vision, retrieval, MoE) to cover a broader range of use cases.

## Why Work Here
- **Mission-Driven & High-Impact**: Work on frontier AI research and products that directly shape how intelligence is deployed in the physical world.
- **Culture of Ownership**: “Leadership sets the destination, but the route is yours to discover and deliver” — high autonomy and trust, with a focus on building over process.
- **Transparent & Meritocratic**: Decisions are documented and traceable; ideas are valued based on evidence, not hierarchy.
- **Global & Diverse Team**: 91 employees across 12 countries; 30% in technical roles, 9% in research. Offices in Cambridge, MA (HQ) and satellite hubs in Japan and Europe.
- **Perks & Environment**:
  - Hybrid/office policy (Cambridge HQ with multiple local offices).
  - Strong emphasis on employee wellbeing: “the company prioritizes the needs and wellbeing of its people.”
  - Continuous learning culture: “everyone is expected to continuously fine-tune their skills.”
- **Recent Open Roles (as of mid-2026)**: ML Research Engineer, Applied ML (RecSys, Vision, Post-Training), Distributed Training Engineer, Solutions Architect, Founding Account Executive, Finance Manager.

## Sources
1. [Liquid AI Official Company Page](https://www.liquid.ai/company)
2. [Liquid AI Official Homepage](https://www.liquid.ai/)
3. [Liquid AI Careers Page](https://jobs.ashbyhq.com/liquid-ai)
4. [Liquid AI LinkedIn](https://www.linkedin.com/company/liquid-ai-inc)
5. [Liquid AI About Page](https://www.liquid.ai/company/about)

## Other roles at Liquid AI

- [Associate General Counsel, Product & Regulatory](https://feeny.ai/job/associate-general-counsel-product-regulatory-liquid-ai-san-francisco-cv1mmvgze9a6) — San Francisco, CA
- [Member of Recruiting Staff - Recruiter](https://feeny.ai/job/member-of-recruiting-staff-recruiter-liquid-ai-san-francisco-5q4n46nad1m3) — San Francisco, CA
- [Strategic Partnerships, Silicon Ecosystem](https://feeny.ai/job/strategic-partnerships-silicon-ecosystem-liquid-ai-san-francisco-0rdqr4ah7ven) — San Francisco, CA
- [People Operations Manager](https://feeny.ai/job/people-operations-manager-liquid-ai-san-francisco-e0f7yan7ee9e) — San Francisco, CA
- [Member of Technical Staff - ML Research Engineer, Pre-Training Data](https://feeny.ai/job/member-of-technical-staff-ml-research-engineer-pre-training-data-liquid-ai-san-wgts2we7mtcg) — San Francisco, CA
- [Office Manager & Executive Assistant](https://feeny.ai/job/office-manager-executive-assistant-liquid-ai-boston-dz1rgs3c6wcf) — Boston, MA
- [Member of Technical Staff - Applied ML, RecSys](https://feeny.ai/job/member-of-technical-staff-applied-ml-recsys-liquid-ai-boston-njmshfbyy3kq) — Boston, MA
- [Member of Technical Staff - Developer Relations](https://feeny.ai/job/member-of-technical-staff-developer-relations-liquid-ai-san-francisco-cxa12bxjfrdn) — San Francisco, CA
- [Strategic Business Development, Life Sciences](https://feeny.ai/job/strategic-business-development-life-sciences-liquid-ai-boston-abmzewrv1rne) — Boston, MA
- [Controller](https://feeny.ai/job/controller-liquid-ai-san-francisco-k2rh6jk06zz6) — San Francisco, CA