Liquid AI
liquid.ai
Actively hiring
AI Research Labs
Foundation Models
Edge AI
As featured in
View 15 jobs
Follow
Overview
News
Technologies
Salaries
Products
People
Growth
Offices
Jobs
Financials
Funding and backers
Total raised
$31.9M
1 round on record
Latest round
$31.9M
Venture round · Dec 2023 · 2 yr ago
Team
43
US Form 5500 (plan participants) · Dec 2025
Hiring now
22
+6 posted in 30 days
Backers
6
ISAI, ISAI
The money's age
Long since its last round
34 months since the last round · and hiring
Momentum
26/100
hiring for its size, in the news
Last sign of life
this month
a posting or a news item
The story so fareach stage dated by its source: the company's releases, the press, registers, filings
Oct 2
First sales or marketing role Member of Go-to-Market Staff
Aug 12
Launched Liquid AI Ships LFM2.5-VL-3B for Faster Vision-Language AI on the Edge · Unite.AI
May 29
On the Hacker News front page Liquid AI reveals 8B-A1B MoE trained on 38T · 245 points
Apr 24
Partnership Mercedes-Benz and Liquid AI Partner to Scale Embedded In-Car Intelligence · businesswire.com
Jun 16, 2025
Partnership G42 and Liquid AI Partner to Deliver Private, Local and Efficient AI Solutions to Enterprises at Scale · businesswire.com
Oct 1, 2024
Launched Liquid AI debuts new LFM-based models that seem to outperform most traditional large language models · SiliconANGLE
Sep 30, 2024
On the Hacker News front page Liquid Foundation Models: Our First Series of Generative AI Models · 183 points
Dec 6, 2023
Raised a round Venture round $31.9M · SEC Form D
2023
Founded
Tractionpublic signals, read monthly
Web presence
top 0.02%
of 133.2M domains by links, Common Crawl
Hacker News stories
29
best: 245 points
Funding rounds
| Round | Date | Amount | Investors | Source |
|---|---|---|---|---|
| Venture round | Dec 2023 | $31.9M | — | SEC Form D |
Registers and programsofficial lists and records that name the company
| Legal entity | Liquid AI, Inc. | SEC Form D |
Founders and leadersfrom filings, registers and the company's site
Louis HuntExecutive OfficerSEC Form D
Mathias LechnerDirector, Executive OfficerSEC Form D
Ramin HasaniExecutive Officer, DirectorSEC Form D
Backed byfrom the funds' portfolios and accelerator catalogs
ISAI 
Link Ventures 
OSS Capital 
PWV 
Untapped Investors in similar startupsfunds that back the companies most like this one
Similar startupsby what they do, their industry and backers
Zyphra is an artificial intelligence research company that develops open foundation models, including the Zamba hybrid state-space language…
ModelBest is a Chinese artificial intelligence company founded in 2022 with roots in Tsinghua University research on large models. It…
Poolside is an artificial intelligence laboratory building foundation models specialised for software engineering rather than general…
Cartwheel is an AI research lab and product company. We build foundation models for human and object motion, and the tools that put them to…
Radical Numerics is a research laboratory working on recursive self improvement of machine learning systems, where models help design the…
Sakana AI is a Tokyo research laboratory taking a nature inspired approach to foundation models, favouring collective intelligence and…
How Liquid AI hires
Truth index
A 95/100
Median time to fill
178 days
Ghost roles
0%
Stale roles
0%
Reposted roles
0%
Liquid AI scores A on the Alion truth index (A is best, E worst), measured over 22 open roles re-checked against its own hiring board: 0% look like ghost listings, 0% have gone stale and 0% are the same role posted again. Its roles close in a median of 178 days. It measures how much of what this employer publishes turns into a real, finite search - not the employer as a workplace. How the index is computed
Overview
Liquid AI is an artificial intelligence company headquartered in Boston, Massachusetts, and founded in 2023 as a spin-off from the MIT Computer Science and Artificial Intelligence Laboratory. The company builds Liquid Foundation Models, an architecture derived from liquid neural networks that aims to match transformer quality at a fraction of the memory and compute. It targets on-device and edge deployment where models must run on phones, vehicles, and embedded hardware rather than in a data center.
News
LFM2.5-DSpark: Up to 3.2x Faster Inference from H100 to MacBook Blog
LFM2.5-DSpark speculative decoding delivers up to 3.2x faster inference on GPU and 2.9x on-device. Day-one llama.cpp and SGLang support.
Read more
Report
Designing Loops for Production-Grade Work Blog
What became standard practice after vibe-coding a production-grade BPE tokenizer trainer without reading a single line of code.
Read more
Report
Liquid AI Ships LFM2.5-VL-3B for Faster Vision-Language AI on the Edge
Liquid AI released LFM2.5-VL-3B on August 12, 2026, a 3.1-billion-parameter open-weight vision-language model built to run on phones, laptops, and single GPUs rather than in a data center. The model, announced on the com...
Read more
Report
LFM2.5-VL-3B: A Better and Faster Vision-Language Model for the Edge - Blog
LFM2.5-VL-3B is Liquid AI's most capable vision-language model, with grounding, screen understanding, and function calling, fast enough to run on-device.
Read more
Report
No cloud, no GPUs, no problem: Liquid AI's new model LFM2.5-2.6B brings powerful AI agents to devices as small as a Raspberry Pi
One test found it performed 3.7 times faster than DeepSeek-V4-Flash, the model has skyrocketed to the top of OpenRouter since its release last week.
Read more
Report
MacPaw teams up with Liquid AI to bring on-device AI to its Mac assistant
Setapp operator MacPaw partners with Liquid AI to build an on-device AI stack for its Eney assistant for fast, private work.
Read more
Report
MacPaw Partners With Liquid AI To Bring On-Device AI To Macs
Liquid Foundation Models and MacPaw's own AI stack will create the first Mac assistant with on-device intelligence, persistent memory and native task execution.
Read more
Report
LFM2.5-2.6B
2.6B dense model trained for agentic workloads, with a 128K context window and native tool calling for on-device agents
Read more
Report
Show more news
Tech stack
Technologies named in job postings at Liquid AI over the last 12 months, by layer, with the share of postings for each.
Technologies in use
68
Postings analysed
18
Stack modernity
79/100AI adopter
Languages
Python22%
C++11%
Rust6%
Frameworks & libraries
PyTorch28%
MLX ML17%
ONNX Runtime17%
DeepSpeed11%
Cloud & platforms
vLLM22%
Hugging Face17%
GitHub11%
Linux6%
AI & ML
LLM28%
VLM11%
AWQ11%
GPTQ6%
Sign in to see how your skills match this stack
Sign In
Full Liquid AI tech stack
68 technologies · by team · pay by technology · changes · similar stacks
People
Louis Hunt
Executive Officer
Mathias Lechner
Director, Executive Officer
Ramin Hasani
Executive Officer, Director
Daniela Rus
Director
Stephen Pagliuca
Director
Joseph Jacks
Director
Names and roles come from public filings, company registers and the company's own site. Is this you? Correct or remove · How we handle this data
Growth
Hiring Momentum
65/100
Growing
Open positions
22
6 opened / 3 closed in 30 days
Median time-to-fill
178 days
faster than 9% of the market
ATS activity
Every ~4 hours
Today
Hiring Dynamics
+100%
Hiring Focus
The percentage next to each role is its share of the company's job openings over the last 90 days; the arrow shows the shift versus the previous period.
AI/ML
46% ▼
Sales
23% ▲
Product
8% ▲
Administrative
8% ▲
Finance
8% ▲
Legal
8% ▲
Actively hiring for Sales (+3 in 30 days)
Activity Timeline
Added Slack to stack
Sep 2026
Added Google Workspace to stack
Sep 2026
Added Linux to stack
Sep 2026
Added Machine Learning to stack
Sep 2026
Added EU AI Act to stack
Sep 2026
Added CUTLASS to stack
Sep 2026
Added Tool Use to stack
Sep 2026
Added LinkedIn to stack
Sep 2026
Added Reward Modeling to stack
Sep 2026
Added Model Distillation to stack
Sep 2026
Added ONNX Runtime to stack
Sep 2026
Added RLHF to stack
Aug 2026
Offices
Where the company hires and what each office is for
Cities
3
Hiring now
3
Countries
2
Busiest office
Boston
Loading the map
Headquarters
Builds here
Office with open vacancies
Tap a pin for the office
Boston
United States
HQ
14 open roles 5 posted in 90 days 64% engineering 50-200 est. staff
hires for AI/ML, Sales, Product
San Francisco
United States
Engineering / R&D
15 open roles 7 posted in 90 days 53% engineering 50-200 est. staff
hires for AI/ML, Product, Sales
Tokyo
Japan
2 open roles 2 posted in 90 days 100% engineering 10-50 est. staff
hires for AI/ML
Jobs
≈ $154k – $323k per year (Estimated) • Hybrid • Full-Time • San Francisco
llama.cpp
Qwen
LoRA
vLLM
Gemma
Fine-tuning
Quantization
Knowledge Distillation
AWQ
GGUF
GPTQ
ONNX
PEFT
QLoRA
TGI
MLX ML
Transformers
PyTorch
LLM
Tokenization
Hugging Face
Edge AI
ExecuTorch
ONNX Runtime
Model Distillation
DevOps
GitHub
Management
Discord
Apply
≈ $158k – $322k per year (Estimated) • Hybrid • Full-Time • Boston
Python
C++
llama.cpp
Quantization
ONNX
MLX ML
Edge AI
ONNX Runtime
Apply
≈ $73k – $167k per year (Estimated) • Hybrid • Full-Time • Tokyo
Reinforcement Learning
Multimodal AI
Knowledge Distillation
Synthetic Data
SFT
Post-training
Model Distillation
Reward Modeling
Machine Learning
Apply
≈ $74k – $167k per year (Estimated) • Hybrid • Full-Time • Tokyo
llama.cpp
vLLM
Fine-tuning
Quantization
Multimodal AI
SGLang
MLX ML
LLM
SFT
Post-training
ONNX Runtime
Apply
≈ $180k – $368k per year (Estimated) • Hybrid • Full-Time • San Francisco
Hadoop
Ray
DevOps
SLURM
Kubernetes
HPC
Linux
Apply
≈ $155k – $325k per year (Estimated) • Hybrid • Full-Time • San Francisco • Boston
Fine-tuning
AI Agents
LLM
Edge AI
Apply
≈ $201k – $411k per year (Estimated) • Hybrid • Full-Time • San Francisco • Boston
Fine-tuning
Reinforcement Learning
Multimodal AI
VLM
Synthetic Data
SFT
Post-training
OCR
Apply
≈ $164k – $335k per year (Estimated) • Hybrid • Full-Time • Boston
Python
Fine-tuning
PyTorch
Recommender Systems
Analytics
A/B Testing
Apply
≈ $202k – $412k per year (Estimated) • Hybrid • Full-Time • San Francisco • Boston
Reinforcement Learning
Multimodal AI
Function Calling
Speech Recognition
LLM
SFT
Post-training
Text-to-Speech
Structured Outputs
Tool Use
Apply
≈ $203k – $414k per year (Estimated) • Hybrid • Full-Time • San Francisco • Boston
vLLM
Fine-tuning
RLHF
SGLang
TensorRT
PyTorch
LLM
Hugging Face
DPO
SFT
Post-training
Apply
≈ $202k – $414k per year (Estimated) • Hybrid • Full-Time • San Francisco • Boston
DeepSpeed
Multimodal AI
Speech Recognition
PyTorch
FSDP
Text-to-Speech
Apply
≈ $139k – $304k per year (Estimated) • Hybrid • Full-Time • Boston
Python
JAX
Multimodal AI
TensorFlow
PyTorch
Machine Learning
Apply
Financials
Total raised
$31.9M
Latest round
Venture - Series Unknown
Funding rounds
1
Funding rounds
| Round | Announced | Amount | |
|---|---|---|---|
| Venture - Series Unknown | 2023 | $31.9M | Details |