---
title: 'Strategic Partnerships, Silicon Ecosystem at Liquid AI'
canonical: 'https://feeny.ai/job/strategic-partnerships-silicon-ecosystem-liquid-ai-san-francisco-0rdqr4ah7ven'
type: 'job'
last_seen: '2026-11-10'
---

# Strategic Partnerships, Silicon Ecosystem at Liquid AI

- **Company:** Liquid AI
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-11-07
- **Last confirmed live:** 2026-11-10
- **Apply:** https://jobs.ashbyhq.com/liquid-ai/04fe3e31-d08e-43f5-bc51-dc7e0a3fede2

## 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 Liquid AI is building the foundation for edge AI, and silicon providers, to emerging companies building the next generation of AI hardware, are a primary path to customers. Our mission is to make Liquid AI a preferred AI foundation across edge computing platforms through deep technical and commercial partnerships. You'll work closely with senior leadership, product, engineering and go-to-market teams, initially leading selected partnerships end to end, with the opportunity to take broader ownership of Liquid's silicon ecosystem as the organization grows.

## What We're Looking For

We need someone who:

- Executes to the finish line: You move fast, act before every data point is in, and measure your work by outcomes (a signed agreement, a shipped product, a live customer), not by the introductions you made.
- Brings structure with judgment: You have an entrepreneurial mindset and a high degree of ownership: you draw on what has worked before, adapt it to a fast-moving startup, and build process where none exists yet.
- Learns the technology out of curiosity: You're passionate about edge AI and ask questions until you understand the technical substance, even when you're not the most technical person in the room.

The Work

- Build and execute strategic silicon partnerships: own relationships with assigned partners, run co-design programs between their product groups and Liquid's teams, and negotiate agreements through to signature.
- Define joint products: work with partners on what their hardware and Liquid's models and agents deliver together, and drive integration, optimization and benchmarking with both engineering teams.
- Drive ecosystem adoption and distribution: take joint products to partner business groups, OEMs and system integrators, and identify the customers to pursue first.
- Develop joint go-to-market: bring Liquid's go-to-market team into partner-sourced opportunities, and lead joint launches, demonstrations and events such as CES.
- Lead cross-functional execution: turn partnership commitments into plans with clear milestones and owners, and resolve technical, commercial and organizational blockers.

## Experience & Capabilities

What you'll need:

- A proven track record of developing and executing strategic partnerships that drive measurable outcomes: signed agreements, shipped integrations, and customers
- Experience working with silicon vendors, hardware platforms, OEMs, or embedded computing ecosystems
- Experience leading commercial negotiations and structuring partnerships involving technical integration, distribution, or joint go-to-market
- Product thinking: defining what a joint offering does, who buys it, and why
- Strong understanding of the AI ecosystem and the evolving roles of AI models, inference software, and hardware platforms
- Ability to work effectively across engineering, product, and business organizations

Helpful, not required:

- Experience with AI inference, machine learning infrastructure, or edge AI
- Familiarity with CPU, GPU, and NPU architectures and their software ecosystems
- Background in AI PCs, mobile devices, automotive, IoT, robotics, or embedded systems
- Existing relationships with major semiconductor companies

What Success Looks Like (Year One)

- At least one silicon partnership taken from early discussions to a signed agreement, a defined joint product, and target customers both companies are pursuing, with Liquid's go-to-market team running the customer conversations and the program moving without your day-to-day involvement

## What We Offer

- Partnerships with real pull: Leading silicon providers are already engaging; you own converting that demand into shipped products, with a path to leading Liquid's ecosystem strategy.
- 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
- [People Operations Manager](https://feeny.ai/job/people-operations-manager-liquid-ai-san-francisco-e0f7yan7ee9e) — San Francisco, CA
- [Strategic Business Development, Startups Lead](https://feeny.ai/job/strategic-business-development-startups-lead-liquid-ai-san-francisco-pg3krfkentsx) — 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