---
title: 'Strategic Business Development, Life Sciences at Liquid AI'
canonical: 'https://feeny.ai/job/strategic-business-development-life-sciences-liquid-ai-boston-abmzewrv1rne'
type: 'job'
last_seen: '2026-10-20'
---

# Strategic Business Development, Life Sciences at Liquid AI

- **Company:** Liquid AI
- **Location:** Boston, MA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-10
- **Last confirmed live:** 2026-10-20
- **Apply:** https://jobs.ashbyhq.com/liquid-ai/a4acca38-93f7-4b4d-8395-6e97a639a755

## Job description

Role: Strategic Business Development, Life Sciences Department: GTM & Partnerships Location: Boston Location Type: Hybrid Employment Type: Full-time

## About Liquid AI

Liquid AI’s mission is to build efficient, general-purpose intelligence at every scale. Founded out of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT in 2023, we build small, efficient, and incredibly fast foundation models that can run directly on the devices all around us—phones, cars, and laptops—with no internet needed. We are scaling and need exceptional people to drive our growth.

## About the role

We are seeking a strategic business development lead to build our life sciences business. You will turn our early work in drug discovery and biology into long-term partnerships and revenue with pharmaceutical, biotech, and research organizations. Our partnership with Insilico Medicine has already produced[LFM2-2.6B-MMAI](https://www.liquid.ai/press/liquid-ai-insilico-medicine-partnership) for drug discovery and[LFM2 Longevity models](https://www.liquid.ai/blog/longevitybench) for aging research. You will drive adoption of Liquid Foundation Models across life sciences, help shape how our scientific and bio models are built and taken to market, and run deals from the first conversation to close. Technical fluency and life sciences expertise is central to this role. Our counterparts are heads of AI, computational chemistry and biology leaders, and R&D executives at pharma and biotech companies. They want to know how a model performs on their data and tasks, where it falls short, and what it takes to deploy on their private infrastructure. You need to be able to drive these conversations credibly, work alongside our research team and engineers on evaluations and deployments, and bring what you learn back into our model and product roadmap. You will be our first business development hire in life sciences and will work directly with the founders and business leadership. This role suits someone who wants to build the playbook while closing first-of-a-kind deals.

## Responsibilities

- Own deals end to end, from identifying and prioritizing pharma, biotech, and research partners through negotiation, close, and delivery. You are accountable for the revenue.
- Source opportunities across drug discovery and life sciences R&D through your network and outreach.
- Manage and expand our existing life sciences partnerships, including our work with Insilico Medicine.
- Negotiate first-of-a-kind agreements that combine licensing, revenue sharing, co-development, and roadmap commitments.
- Lead technical and scientific conversations with heads of AI, computational scientists, and R&D leaders, and work with our scientists and engineers on technical deep-dives, proofs of concept, benchmarks, and deployment planning.
- Be the voice of the market internally. Bring back objections, competitive intelligence, pricing feedback, and emerging use cases that should influence our product, model roadmap, and positioning.
- Build our life sciences GTM engine. Define how we evaluate and qualify partners, shape our external messaging, and develop the infrastructure and operating cadences that will let our team and business scale.

Desired experience

- 10+ years in business development, partnerships, or corporate development in pharma, biotech, or life sciences technology, with a record of deals that moved revenue.
- Recent deal experience bringing AI/ML, computational platforms, or data products into pharma and biotech R&D.
- Deep knowledge of drug discovery and development, and of how pharma and biotech companies evaluate, buy, and partner on R&D technology.
- High technical and scientific fluency. You understand what foundation models can do and how that translates into R&D workflows, and you can work credibly with scientists and engineers on both sides of the table.
- Demonstrated success structuring and personally negotiating complex agreements with senior executives, such as R&D collaborations or platform licensing deals, including multi-year deals with interlocking terms, often several at once.
- Experience leading cross-functional teams across Product, Engineering, Legal, and Finance to bring an agreement from structuring through signature and delivery.
- Relationships with R&D, computational, and data science leaders at pharma and biotech companies, and a record of sourcing your own opportunities.
- Experience at an early-stage or growth-stage company where you helped build the motion rather than run an established one.

## What we offer

- Compensation: Competitive base salary + variable compensation 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

- [Developer Relations](https://feeny.ai/job/developer-relations-liquid-ai-san-francisco-cxa12bxjfrdn) — San Francisco, CA
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- [Strategic Business Development](https://feeny.ai/job/strategic-business-development-liquid-ai-san-francisco-xb9vz7j1b4v8) — San Francisco, CA
- [Member of Go-to-Market Staff](https://feeny.ai/job/member-of-go-to-market-staff-liquid-ai-north-america-l-san-francisco-boston-3h9m36kbxe17) — North America L San Francisco Boston, OR
- [Office Manager/Executive Assistant](https://feeny.ai/job/office-manager-executive-assistant-liquid-ai-boston-w7qpd15rv7be) — Boston, MA
- [Associate General Counsel, Product & Regulatory](https://feeny.ai/job/associate-general-counsel-product-regulatory-liquid-ai-san-francisco-cv1mmvgze9a6) — San Francisco, CA
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- [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
- [Product Manager](https://feeny.ai/job/product-manager-liquid-ai-san-francisco-jd34b9k8eehq) — San Francisco, CA