Goodfire
goodfire.com
Actively hiring
Explainable AI (XAI)
AI Safety & Alignment
AI Research Labs
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Products
People
Growth
Offices
Jobs
Financials
Funding and backers
Total raised
$207M
3 rounds on record
Latest round
$150M
Series B · Feb 2026 · 8 mo ago
Team
201-500
employees, estimated range
Hiring now
25
open roles
Backers
6
South Park Commons, Juniper
The money's age
Fresh money
8 months since the last round · hiring slowed
Momentum
35/100
in the news, fresh money
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
Aug 6
First role in United Kingdom Research Scientist (London)
Feb 9
Board appointment Yan-David Erlich, Director · SEC Form D
Feb 6
Raised a round Series B $150M · SiliconANGLE
Apr 17, 2025
Raised a round Series A $50M · led by Menlo Ventures · PRNewswire
Aug 14, 2024
Raised a round Seed $7M
2023
Founded
Tractionpublic signals, read monthly
Web presence
top 11%
of 133.2M domains by links, Common Crawl
Hacker News stories
2
best: 2 points
Funding rounds
| Round | Date | Amount | Investors | Source |
|---|---|---|---|---|
| Series B | Feb 2026 | $150M | — | SiliconANGLE |
| Series A | Apr 2025 | $50M | Menlo Ventures lead | PRNewswire |
| Seed | Aug 2024 | $7M | — | businesswire.com |
Registers and programsofficial lists and records that name the company
| Legal entity | Goodfire AI, Inc. | SEC Form D |
Founders and leadersfrom filings, registers and the company's site
Eric HoExecutive Officer, DirectorSEC Form D
Backed byfrom the funds' portfolios and accelerator catalogs
South Park Commons 
Lightspeed Venture Partners 
Menlo Ventures 
Salesforce Ventures Investors in similar startupsfunds that back the companies most like this one
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How Goodfire hires
Truth index
C 57/100
Ghost roles
72%
Stale roles
0%
Reposted roles
0%
Goodfire scores C on the Alion truth index (A is best, E worst), measured over 25 open roles re-checked against its own hiring board: 72% look like ghost listings, 0% have gone stale and 0% are the same role posted again. 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
Goodfire is an artificial intelligence research company focused on mechanistic interpretability, building tools and methods to understand and edit the internal representations of neural networks. Founded in 2023, it develops the Ember interpretability platform, publishes research on model internals and partners with AI developers and scientific organisations to make models more reliable and safe. The company is headquartered in San Francisco, California, United States.
News
Models know when they're reward hacking - and we can catch them at scale - Goodfire
We found a clear internal signal in models that accompanies reward hacking, and built probes that detect it - enabling efficient, real-time detection of reward hacking at scale.
Read more
Report
Base Labs launches an open-weight AI safety partnership with Hugging Face and Goodfire
Base Labs, the research group Baseten spun up earlier this year, will develop and publish methods for training and monitoring open models.
Read more
Report
Get Silico - Individuals
Run long-horizon, asynchronous experiments on frontier infrastructure and compute.
Read more
Report
Report
Neural Geometry in Vision Models with Block-Sparse Featurizers
We introduce Block-Sparse Featurizers (BSF), a family of methods to decompose a model's activations into multidimensional subspaces rather than single directions. Applied to vision models, we find that BSFs find interpretable, multidimensional features wh
Read more
Report
Neural Geometry in Vision Models with Block-Sparse Featurizers
We introduce Block-Sparse Featurizers (BSF), a family of methods to decompose a model's activations into multidimensional subspaces rather than single directions. Applied to vision models, we find that BSFs find interpretable, multidimensional features wh
Read more
Report
Predictive Data Debugging: Reveal and Shape What Your Model Learns, Before You Train
Given a preference dataset, we can accurately predict which behaviors RL will amplify or suppress before you train, trace them back to the responsible data, and reshape the dataset and/or training process to prevent undesired effects.
Read more
Report
Predictive Data Debugging: Reveal and Shape What Your Model Learns, Before You Train
Given a preference dataset, we can accurately predict which behaviors RL will amplify or suppress before you train, trace them back to the responsible data, and reshape the dataset and/or training process to prevent undesired effects.
Read more
Report
Can SAEs Capture Neural Geometry?
AKA, how to use straight lines to capture curved geometry in neural networks
Read more
Report
Can SAEs Capture Neural Geometry?
AKA, how to use straight lines to capture curved geometry in neural networks
Read more
Report
Show more news
Tech stack
Technologies named in job postings at Goodfire over the last 12 months, by layer, with the share of postings for each.
Technologies in use
15
Postings analysed
24
Stack modernity
81/100AI adopter
Languages
Python17%
Frameworks & libraries
PyTorch21%
JAX8%
Cloud & platforms
OpenAI100%
AWS4%
Azure4%
GCP4%
AI & ML
LLM8%
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Full Goodfire tech stack
15 technologies · by team · pay by technology · changes · similar stacks
Salary insights
Compensation ranges based on this company's open jobs
Median
$400k
Typical range
$315k – $600k
Open positions
15
9
Jobs
Senior
22.2%
Staff
55.6%
Architect
22.2%
| Level | Jobs | Median | Typical range |
|---|---|---|---|
| Senior | 2 | $400k | $400k |
| Staff | 5 | $375k | $350k – $600k |
| Architect | 2 | $475k | $450k – $500k |
Highest paying role
Research Lead, Training
$600k
Normalized to USD per year
All salaries at Goodfire
By role, level and city, against the market · 15 jobs with pay
People
Eric Ho
Executive Officer, Director
Deedy Das
Director
Nnamdi Iregbulem
Director
Daniel Kang
Director
Tom McGrath
Director
Daniel Balsam
Director
Yan-David Erlich
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
51/100
Stable
Open positions
25
0 opened / 2 closed in 30 days
Median time-to-fill
245 days
faster than 7% of the market
ATS activity
Every ~3 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
29% ▼
HR
29% ▼
Security
14% ▲
Administrative
14% ▼
Legal
14% ▲
Activity Timeline
Added Machine Learning to stack
Sep 2026
Added LLM to stack
Sep 2026
Added AI Agents to stack
Sep 2026
Added Agentic Workflows to stack
Sep 2026
Added Post-training to stack
Sep 2026
Added Slack to stack
Sep 2026
Added Google Workspace to stack
Sep 2026
Added Interpretability to stack
Sep 2026
Added Least Privilege to stack
Aug 2026
Added OpenAI to stack
Aug 2026
Offices
Where the company hires and what each office is for
Cities
2
Hiring now
2
Countries
2
Busiest office
San Francisco
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Headquarters
Builds here
Office with open vacancies
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San Francisco
United States
HQ
San Francisco
24 open roles 6 posted in 90 days 33% engineering 200-500 est. staff $408k Avg Salary
hires for AI/ML, HR, Marketing
London
United Kingdom
Engineering / R&D
London
1 open roles 1 posted in 90 days 100% engineering 10-50 est. staff $397k Avg Salary
hires for AI/ML
Jobs
≈ $132k – $268k per year (Estimated) • In office • 2+ years exp • San Francisco
OpenAI
Interpretability
Machine Learning
Apply
≈ $257k – $525k per year (Estimated) • In office • Full-Time • San Francisco
Python
OpenAI
Interpretability
Machine Learning
Apply
$200k – $350k per year • In office • 5+ years exp • San Francisco
AI Agents
OpenAI
Interpretability
DevOps
CI/CD
Cybersecurity
SOC 2
Apply
$220k – $315k per year • In office • PhD • San Francisco
Python
PyTorch
OpenAI
Interpretability
Apply
$220k – $315k per year • In office • PhD • San Francisco
Python
PyTorch
OpenAI
Interpretability
Apply
$200k – $325k per year • In office • San Francisco
Python
Fine-tuning
JAX
PyTorch
OpenAI
Interpretability
Apply
$200k – $400k per year • In office • PhD • London
Python
PyTorch
OpenAI
Interpretability
Apply
$400k – $600k per year • In office • San Francisco
OpenAI
Post-training
Interpretability
Apply
$200k – $400k per year • In office • PhD • San Francisco
Python
PyTorch
OpenAI
Interpretability
Apply
$200k – $400k per year • In office • 5+ years exp • San Francisco
Python
PyTorch
OpenAI
Interpretability
Machine Learning
Apply
$300k – $450k per year • In office • 10+ years exp • San Francisco
JAX
PyTorch
OpenAI
Interpretability
Machine Learning
Apply