---
title: 'Member of Recruiting Staff - Technical Recruiter at Liquid AI'
canonical: 'https://feeny.ai/job/member-of-recruiting-staff-technical-recruiter-liquid-ai-san-francisco-bsjt2w1p7n1d'
type: 'job'
last_seen: '2026-09-15'
---

# Member of Recruiting Staff - Technical Recruiter at Liquid AI

- **Company:** Liquid AI
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-06-10
- **Last confirmed live:** 2026-09-15
- **Apply:** https://jobs.ashbyhq.com/liquid-ai/62d07129-e624-4140-96b6-bfd80d4a4a95

## 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 hiring fast across the business, and our high-output recruiting team is how we win the talent that defines us. This is a full-cycle role in San Francisco, owning hiring across the full spectrum: engineering and research, product, solutions architecture, GTM, and G&A. Recruiting here is a highly ambiguous, build-from-scratch environment. We are hiring for most of these roles for the first time, so you will define brand-new roles, build the rubrics, coach stakeholders, and bring in exceptional people. You will run your searches with high agency and minimal supervision, with a manager who will still mentor you.

## What We're Looking For

We need someone who:

- Operates as a talent partner, not just a recruiter: You measure yourself by what is best for the business, not seats filled.
- Builds in ambiguity: You are energized by undefined problems and create structure where there is none.
- Thinks strategically and proactively: You read the data, anticipate where a search will stall, and unblock it before it becomes a problem, rather than reacting after the fact.
- Prioritizes ruthlessly: In a high-noise environment with endless problems to solve, you know exactly where your time creates the most leverage, and you protect it.
- Brings genuine passion for the craft: You are eager to learn and grow. You may not have the full strategic scope on day one, but it is obvious you will get there.
- Runs autonomously, with high agency: You thrive with minimal supervision, while still wanting a manager who will mentor and stretch you.

The Work

- Own full-cycle hiring across the spectrum as the in-person anchor in San Francisco, running on-sites and closing senior and executive hires face-to-face.
- Coach stakeholders and partner with senior leaders and the C-suite to define brand-new roles before they kick off.
- Identify the best talent: go beyond LinkedIn and build the evidence for why a candidate is the best, not just available.
- Build rigorous, role-specific evaluation from scratch: define what 'good' looks like, assessing for the attributes and values that predict success, not just skills, and make the process itself a reason candidates want to join.
- Win and close the candidates that matter, and prioritize ruthlessly: sharpen the value proposition, read the data to unblock stalling searches before they become problems, and gather market intel.
- Close the loop on quality and run a clean operation: measure quality of hire and run look-backs, keep Ashby data reportable, document process in Notion, and use AI-enabled workflows to move faster.

Desired Experience Must-have:

- Proven depth in full-cycle recruiting for research, engineering, or other deeply technical roles, with the seniority to own complex searches end-to-end.
- A track record of winning competitive closes: competing offers, equity education, total-compensation narrative, creative engagement, and in-person closes
- Builder in ambiguity: you have defined roles, rubrics, and evaluation processes from scratch and coached hiring managers, including first-timers
- Strong ATS discipline (Ashby or comparable) plus recruiting-data rigor: structured screens, scorecards, calibrated loops, and accurate, reportable metrics (time-to-fill, pass-through, quality of hire)
- Based in San Francisco and able to work from the office 4+ days per week and host candidate onsites

Nice-to-have:

- AI / ML or deep-tech recruiting experience
- Early-stage (seed to Series C) team-building experience, where you helped build the motion rather than execute a mature playbook
- Experience building quality-of-hire and retention loops: onboarding check-ins, hire look-backs, and calibration back into evaluation
- Demonstrated range across product, GTM, G&A, and customer-facing technical roles (or a clear, evidenced ability to flex into them)

What Success Looks Like (Year One)

- You own and close a full book across engineering, product, solutions architecture, GTM, and G&A end-to-end
- You run independently, trusted with judgment calls, sustaining hiring quality and pace
- New and ambiguous roles get clear, role-specific rubrics and evaluation loops, and hiring managers are measurably better at hiring because of how you coach them.
- P0 roles close faster, and you have quality-of-hire and look-back loops running that feed back into our evaluation.

## What We Offer

- Real ownership with a direct mentor and room to grow: Run your searches end to end, and your judgment directly shapes who joins Liquid as we scale.
- Compensation: Competitive base salary with equity in a unicorn-stage company
- Health: We pay 100% of medical, dental, and vision premiums for employees and dependents
- Financial: 401(k) matching up to 4% of base pay
- Time Off: Unlimited PTO plus company-wide Refill Days throughout the year

## 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-north-america-l-san-cv1mmvgze9a6) — North America L San Francisco CA OR Cambridge, MA
- [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
- [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