--- title: 'Associate General Counsel, Product & Regulatory at Liquid AI' canonical: 'https://feeny.ai/job/associate-general-counsel-product-regulatory-liquid-ai-north-america-l-san-cv1mmvgze9a6' type: 'job' last_seen: '2026-09-15' --- # Associate General Counsel, Product & Regulatory at Liquid AI - **Company:** Liquid AI - **Location:** North America L San Francisco CA OR Cambridge, MA - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-09-12 - **Last confirmed live:** 2026-09-15 - **Apply:** https://jobs.ashbyhq.com/liquid-ai/b9c061cc-f976-4d87-88b4-722217472373 ## Job description Liquid AI is an efficiency-first foundation model company. We build highly capable AI models designed to operate across the full range of environments—from cloud infrastructure to phones, vehicles, and other edge devices. Opportunity Liquid AI is seeking an experienced Associate General Counsel to lead our product counseling and AI regulatory work. Reporting to the Chief Legal Officer, this person will work closely with our product, research, and engineering teams as they develop and deploy new AI models and products. The role requires someone who can understand novel and unsettled legal issues, make practical decisions, and translate those decisions into things the company can actually do. The job is not simply to monitor regulatory developments or write policies. It is to determine what they mean for Liquid’s products and help the company act. Core Responsibilities - Own legal support for the development, release, and deployment of Liquid’s models and products. - Advise product, research, and engineering teams on AI regulation, privacy, data use, intellectual property, model safety, security, and product claims. - Lead Liquid’s response to the EU AI Act and other emerging AI laws, including the practical controls, documentation, and product decisions needed for compliance. - Advise on training and evaluation data, synthetic data, model outputs, open-source and open-weight releases, fine-tuning, and customer deployments. - Support the commercial team on product and regulatory issues arising in strategic customer and partnership agreements. Required Capabilities - At least 8 years of relevant legal experience, including meaningful in-house experience advising technology product teams. - Strong background in AI regulation, privacy, data governance, intellectual property, or related technology issues. - Ability to understand how Liquid’s products work and give clear, practical, risk-based advice. - Ability to operate independently, identify issues before they become problems, and drive work through completion. - Comfort making decisions in areas where the law is new, unsettled, or simply does not provide a clean answer. - Clear, concise writing. The Right Candidate - Thinks from first principles and is genuinely interested in technology. - Wants to work directly with the people building products—not review them from a distance. - Exercises judgment rather than reflexively escalating, documenting, or avoiding risk. - Is comfortable taking ownership, being decisive, and occasionally being wrong. - High integrity, optimistic, and low ego. - Healthy sense of humor. ## 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 - [Member of Technical Staff - Inference Systems](https://feeny.ai/job/member-of-technical-staff-inference-systems-liquid-ai-boston-n21ddyv32pqs) — Boston, MA - [Member of Technical Staff - ML Scientist, Japanese Multimodal](https://feeny.ai/job/member-of-technical-staff-ml-scientist-japanese-multimodal-liquid-ai-tokyo-b1sxex046dg8) — Tokyo, Japan - [Member of Technical Staff - Applied ML, Japanese Multimodal](https://feeny.ai/job/member-of-technical-staff-applied-ml-japanese-multimodal-liquid-ai-tokyo-hv79bwy6nmkk) — Tokyo, Japan - [Member of Technical Staff - GPU Infrastructure Engineer](https://feeny.ai/job/member-of-technical-staff-gpu-infrastructure-engineer-liquid-ai-san-francisco-5qry0efpcqvv) — San Francisco, CA - [Member of Technical Staff - Embedded ML Engineer (Audio/Omni)](https://feeny.ai/job/member-of-technical-staff-embedded-ml-engineer-audio-omni-liquid-ai-san-9pyn1p2pa7t5) — San Francisco, CA - [Product Manager](https://feeny.ai/job/product-manager-liquid-ai-san-francisco-jd34b9k8eehq) — San Francisco, CA - [Member of Recruiting Staff - Technical Recruiter](https://feeny.ai/job/member-of-recruiting-staff-technical-recruiter-liquid-ai-san-francisco-bsjt2w1p7n1d) — San Francisco, CA - [Solutions Architect](https://feeny.ai/job/solutions-architect-liquid-ai-san-francisco-qbvwa5nr2h91) — San Francisco, CA - [Member of Technical Staff - Post Training, Applied (Vision)](https://feeny.ai/job/member-of-technical-staff-post-training-applied-vision-liquid-ai-san-francisco-vtjy7ncbazk1) — San Francisco, CA - [Member of Technical Staff - Applied ML, RecSys](https://feeny.ai/job/member-of-technical-staff-applied-ml-recsys-liquid-ai-boston-njmshfbyy3kq) — Boston, MA