Lila Sciences
lila.ai
Actively hiring
Materials Science & Nanotechnology
Laboratory & Pharmaceutical Robotics
AI Research Labs
AI for Science
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Overview
News
Technologies
Salaries
Products
People
Growth
Offices
Jobs
Financials
Funding and backers
Total raised
$200M
1 round on record
Latest round
$200M
Venture round · Mar 2025 · 19 mo ago
Team
201-500
employees, estimated range
Hiring now
101
+20 posted in 30 days
Backers
2
Flagship Pioneering, General Catalyst
The money's age
Due for its next round
19 months since the last round · and hiring
Momentum
33/100
hiring for its size, a new city, 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
Tractionpublic signals, read monthly
Web presence
top 2%
of 133.2M domains by links, Common Crawl
Hacker News stories
1
best: 4 points
Funding rounds
| Round | Date | Amount | Investors | Source |
|---|---|---|---|---|
| Venture round | Mar 2025 | $200M | — | SiliconANGLE |
Backed byfrom the funds' portfolios and accelerator catalogs
Flagship Pioneering 
General Catalyst Investors in similar startupsfunds that back the companies most like this one
Similar startupsby what they do, their industry and backers
Lila Sciences builds scientific superintelligence by pairing large models with autonomous laboratories that run their own experiments…
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Accelerate R&D with adaptive machine learning. Cut experiments by 50-80%. Trusted by NASA, Boeing and Johnson Matthey.
LabsCubed builds lab automation for materials testing. See how CubeOne (rubber) and CubeTen (plastics) automated tensile testing machines…
How Lila Sciences hires
Truth index
A 89/100
Median time to fill
70 days
Ghost roles
0%
Stale roles
25%
Reposted roles
0%
Lila Sciences scores A on the Alion truth index (A is best, E worst), measured over 48 open roles re-checked against its own hiring board: 0% look like ghost listings, 25% have gone stale and 0% are the same role posted again. Its roles close in a median of 70 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
Lila Sciences is an American company launched publicly in 2025 out of Flagship Pioneering with the aim of building what it calls scientific superintelligence: artificial intelligence systems that generate hypotheses and then test them in the company's own automated laboratories. Its distinguishing feature is the closed loop between model and experiment, since most scientific machine learning is limited by the fact that the data it needs has never been generated. Headquartered in Cambridge, Massachusetts and funded at an unusually large scale for a company at this stage, it is working across life sciences and materials chemistry rather than committing to a single field.
News
Lila Sciences' swollen first round, and other biofinancings
AI-powered autonomous lab firm Lila Sciences upsizes its Series A to $350m, heading a bumper week for new biotech financings.
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Report
Welcoming New Partners in Our Mission to Build Scientific Superintelligence Lila
Lila Sciences announced a major Series A milestone, raising $235M to advance its mission of building scientific superintelligence.
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Report
Lila Moss hits Paris Fashion Week in totally see-through top
Lila Moss wore a completely sheer top and ruffled skirt at Paris Fashion Week.
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Report
Lila Sciences raises $200M to accelerate autonomous scientific research
Lila Sciences raises $200M to accelerate autonomous scientific research - SiliconANGLE
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Report
How to raise second-gen kids who can outcompete H1B visa holders
Note: This post has no advice about raising ultra-competitive kids.
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Tech stack
Technologies named in job postings at Lila Sciences over the last 12 months, by layer, with the share of postings for each.
Technologies in use
159
Postings analysed
107
Stack modernity
81/100AI adopter
Languages
Python61%
SQL15%
TypeScript12%
C++4%
Frameworks & libraries
PyTorch21%
FastAPI14%
Dagster10%
JAX9%
Databases
PostgreSQL3%
DuckDB2%
BigQuery1%
ClickHouse1%
Cloud & platforms
AWS26%
Kubernetes23%
GitHub Actions14%
Prefect10%
AI & ML
LLM14%
AWQ1%
GPTQ1%
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Full Lila Sciences tech stack
159 technologies · by team · pay by technology · changes · similar stacks
Salary insights
Compensation ranges based on this company's open jobs
Median
$256k
Typical range
$101k – $500k
Open positions
93
86
Jobs
Junior
3.5%
Middle
14%
Senior
38.4%
Staff
18.6%
Principal
15.1%
Architect
10.5%
| Level | Jobs | Median | Typical range |
|---|---|---|---|
| Junior | 3 | $109k | $101k – $144k |
| Middle | 12 | $170k | $103k – $304k |
| Senior | 33 | $240k | $118k – $390k |
| Staff | 16 | $272k | $172k – $298k |
| Principal | 13 | $336k | $208k – $420k |
| Architect | 9 | $256k | $224k – $500k |
Highest paying role
Head of Software Product
$500k
Normalized to USD per year
All salaries at Lila Sciences
By role, level and city, against the market · 93 jobs with pay
Products
Materials Science Programmes
Discovery of catalysts, materials and chemical processes. Feedback loops here are far shorter than in biology, which makes materials a better early test of whether the method actually produces results.
lila.ai
Life Sciences Programmes
Discovery work in biology and therapeutics run on the platform. Applying the approach to drug discovery is the most valuable use if it works and the hardest to validate, given how long clinical evidence takes.
lila.ai
Autonomous Laboratories
Robotic laboratories that execute the experiments the models design without human intervention. Closing the loop between hypothesis and result is the whole thesis, and it requires owning the physical capability rather than outsourcing it.
lila.ai
Scientific Superintelligence Platform
Models that propose experiments and interpret their results rather than only analysing existing data. Most scientific machine learning is constrained by data that has never been generated, which is what the automated laboratories are for.
lila.ai
Growth
Hiring Momentum
68/100
Growing
Open positions
100
21 opened / 27 closed in 30 days
Median time-to-fill
70 days
faster than 19% 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.
Science & Research
27% ▲
AI/ML
20%
Robotics
7% ▲
Sales
6% ▼
Product
5% ▼
Operations
5% ▲
Actively hiring for Science & Research (+7 in 30 days)
Activity Timeline
New location: London
Oct 2026
Added ROS to stack
Oct 2026
Added Fusion 360 to stack
Oct 2026
Added Motion Planning to stack
Oct 2026
Added Isaac Sim to stack
Oct 2026
Added Gazebo to stack
Oct 2026
Added ROS2 to stack
Sep 2026
Added Nav2 to stack
Sep 2026
Added Okta to stack
Sep 2026
Added Microsoft Entra ID to stack
Sep 2026
Added MATLAB to stack
Sep 2026
Added Scrum to stack
Sep 2026
Offices
Where the company hires and what each office is for
Cities
3
Hiring now
3
Countries
2
Busiest office
Cambridge
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Headquarters
Builds here
Office with open vacancies
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Cambridge
United States
HQ
One Charles Park, Cambridge, MA
86 open roles 67 posted in 90 days 57% engineering 200-500 est. staff $236k Avg Salary
hires for Science & Research, Backend, Product
San Francisco
United States
Plant / site
One Charles Park, Cambridge, MA
44 open roles 17 posted in 90 days 68% engineering 50-200 est. staff $306k Avg Salary
hires for AI/ML, Backend, Leadership
London
United Kingdom
1 open roles 1 posted in 90 days 100% engineering 1-10 est. staff $218k Avg Salary
hires for Science & Research
Jobs
$180k – $298k per year • In office • Bachelor's Degree • Cambridge • San Francisco
Python
FastAPI
AI/ML
Multimodal AI
Function Calling
AI Agents
PyTorch
RAG
Hugging Face
Agentic Workflows
Tool Use
Machine Learning
DevOps
CI/CD
Apply
$148k – $240k per year • In office • Cambridge • San Francisco
Python
Dagster
MLFlow
AI Agents
LLM
Ray
Flyte
DevOps
CI/CD
Kubernetes
Apply
$140k – $197k per year • In office • 5+ years exp • PhD • Cambridge
AI Agents
Apply
≈ $186k – $350k per year (Estimated) • In office • Cambridge
Nav2
ROS2
Isaac Sim
Motion Planning
Apply
≈ $128k – $309k per year (Estimated) • In office • Contractor • Cambridge
ROS
Design
SolidWorks
Fusion 360
Apply
≈ $156k – $313k per year (Estimated) • In office • Cambridge
Nav2
ROS2
Gazebo
Isaac Sim
Motion Planning
Apply
$252k – $336k per year • In office • 2+ years exp • Cambridge • San Francisco
Python
RLHF
Multimodal AI
AI Agents
PyTorch
Mixture of Experts
DPO
SFT
PPO
GRPO
Post-training
LLM Evaluation
Machine Learning
Apply
$180k – $298k per year • In office • 1+ year exp • Cambridge • San Francisco
Python
RLHF
Multimodal AI
AI Agents
PyTorch
Mixture of Experts
DPO
SFT
PPO
GRPO
Post-training
LLM Evaluation
Machine Learning
Apply
$180k – $280k per year • In office • 5+ years exp • San Francisco
Python
Go
TypeScript
AI Agents
DevOps
Terraform
Helm
GitHub Actions
GitLab CI
CI/CD
AWS
Kubernetes
Apply
$148k – $210k per year • In office • 8+ years exp • Cambridge
Python
Ray
Machine Learning
DevOps
GitHub Actions
Prometheus
CI/CD
GitOps
ArgoCD
Kubernetes
Grafana
Apply
$76k – $109k per year • In office • Cambridge
Python
Nav2
ROS2
Apply
$192k – $272k per year • In office • 8+ years exp • Bachelor's Degree • San Francisco
Python
FastAPI
AI/ML
Model Context Protocol
AI Agents
DevOps
Terraform
GCP
AWS
Kubernetes
Platform Engineering
Cybersecurity
SOC 2
HIPAA
FedRAMP
Apply
Financials
Total raised
$200M
Latest round
Venture - Series Unknown
Funding rounds
1
Funding rounds
| Round | Announced | Amount | |
|---|---|---|---|
| Venture - Series Unknown | 2025 | $200M | Details |