Overview
News
Technologies
Salaries
Products
People
Growth
Jobs
Financials
Overview
Snorkel AI was founded in 2019 by Stanford researchers who developed programmatic labelling, where subject matter experts write rules that generate training data instead of annotating examples by hand. Its platform now covers data curation, model fine-tuning and expert evaluation for enterprise and frontier model builders. Banks, insurers and government agencies use it to specialise models on proprietary knowledge.
News
Why Frontier Agents Fail Real Engineering Work: Two Terminal-Bench 3.0 Task Deep Dives
Terminal-Bench 3.0 (formerly Frontier-Bench) recently launched, built to track what AI agents can and can't do across real computer work. Terminal-Bench 2.1 has been saturating, with top agents reaching 84%; on Terminal-Bench 3.0, the best model, Claude O
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Report
Continual Learning Bench: measuring whether AI systems actually improve with experience
At our latest Snorkel AI Reading Group, Parth Asawa (UC Berkeley Sky Computing Lab) presented Continual Learning Bench, the first expert-validated benchmark designed to measure whether LLM-based systems genuinely improve through sequential experience. CL-
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Report
Train-to-Test (T²) Scaling Laws: Why Reasoning Models Should Be Overtrained
At our latest Snorkel AI Reading Group, Nicholas Roberts presented Test-Time Scaling Makes Overtraining Compute-Optimal, work coauthored with Sungjun Cho, Zhiqi Gao, Tzu-Heng Huang, Albert Wu, Gabriel Orlanski, Avi Trost, Kelly Buchanan, Aws Albarghouthi,
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Report
Milestone-Based Evaluation and Training for Long-Horizon AI Agents
Long-horizon agents operate across many dependent states and transitions, often spanning multiple tools, environments, and periods of external feedback. The difficulty comes from preserving coherent progress as earlier decisions constrain later actions. A
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Report
Enterprise environments and training AI agents for real-world workflows
Most agent benchmarks still evaluate a thin slice of the job. The agent receives a task, produces an answer, gets scored, and the episode ends. Enterprise workflows work differently. An underwriting agent may need to read policy documents, inspect custome
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Report
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Technologies
Tech DNA
Python
SQL
JavaScript
PyTorch
Ray
CrewAI
Chroma
Weaviate
ClickHouse
AWS
Azure
GCP
LLM
Claude
AI/ML
Python
SQL
Snorkel
LLM
Human-in-the-Loop
Fine-tuning
AI Agents
Synthetic Data
CI/CD
Prompt Engineering
Scikit-learn
Reinforcement Learning
Terraform
AWS
PyTorch
RAG
Ray
Spark
Multimodal AI
Azure
GCP
Chroma
FAISS
Weaviate
CrewAI
LangGraph
LlamaIndex
Transformers
LangChain
Claude
Streamlit
NLP
Hugging Face
Mypy
Kubernetes
Amazon ECS
IAM
ClickHouse
Amazon Redshift
Snowflake
Claude Code
Cursor
Dagster
dbt
Prefect
RLHF
NumPy
Pandas
TensorFlow
Data Augmentation
TPU
Anthropic
Model Context Protocol
OpenAI
Recommender Systems
DPO
Post-training
Red Teaming
Function Calling
Buildkite
CircleCI
Amazon EKS
OpenTelemetry
SLI/SLO/SLA
Docker
Amazon EventBridge
Amazon S3
Security
JavaScript
PowerShell
Go
SOC 2
Auth0
ISO 27001
Least Privilege
Zero Trust
FedRAMP
Crowdstrike
Okta
GDPR
HIPAA
CIS Benchmarks
HashiCorp Vault
NIST CSF
SBOM
Threat Modeling
Vault
Frontend
Node JS
TypeScript
Next.js
React.js
Redux
Tailwind CSS
Other
FastAPI
Pytest
Rollup
Rest API
GraphQL
Plotly
ETL/ELT
A/B Testing
State Management
Google Workspace
Jira
Notion
Slack
Zapier
Stack modernity
78/100
How modern this stack is, based on technology relevance, AI adoption and the share of legacy tools.
In-demand technologies
Snorkel
24 jobs
Required
$320k
Median
LLM
16 jobs
Required
$320k
+60% vs market
Python
15 jobs
Required
$320k
+78% vs market
Human-in-the-Loop
7 jobs
Required
$320k
+45% vs market
AI Agents
6 jobs
Required
$300k
+36% vs market
Fine-tuning
6 jobs
Required
$300k
+30% vs market
Synthetic Data
5 jobs
Required
$320k
+14% vs market
CI/CD
5 jobs
Required
Salary medians are calculated from this company's open jobs and compared with the market.
Industry adoption
Python
20%
AWS
16%
JavaScript
15%
CI/CD
15%
SQL
14%
AI Agents
14%
Share of companies in the same industry that use each technology.
Stack changes
Amazon ECS
Aug 2026
Function Calling
Aug 2026
Red Teaming
Aug 2026
Post-training
Aug 2026
DPO
Aug 2026
A/B Testing
Aug 2026
IAM
Aug 2026
ETL/ELT
Aug 2026
Technologies recently added to or removed from this company's stack - a signal of tech migrations and new initiatives.
Jobgether
Salesforce
Booz Allen Hamilton
Accenture
Weekday
Adobe
Salary insights
Compensation ranges based on this company's open jobs
Median
$320k
Typical range
$200k – $403k
Open positions
14
14
Jobs
Middle
14.3%
Senior
7.1%
Staff
42.9%
Architect
35.7%
| Level | Jobs | Median | Typical range |
|---|---|---|---|
| Middle | 2 | $300k | $300k |
| Senior | 1 | $320k | $320k |
| Staff | 6 | $310k | $200k – $320k |
| Architect | 5 | $350k | $300k – $403k |
Highest paying role
Head of Forward Deployed Engineering
$403k
Normalized to USD per year
Growth
Hiring Momentum
30/100
Slowing
Open positions
24
0 opened / 0 closed in 30 days
Median time-to-fill
325 days
faster than 3% of the market
ATS activity
Every ~8 hours
08/31/2026
Hiring Dynamics
0%
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.
Data Science
42% ▼
Backend
33% ▲
Executive
17% ▼
DevOps
8% ▲
Actively hiring for Backend (+4 in 30 days)
Activity Timeline
Added SLI/SLO/SLA to stack
Aug 2026
Added Rollup to stack
Aug 2026
Added Plotly to stack
Aug 2026
Added RLHF to stack
Aug 2026
Added Multimodal AI to stack
Aug 2026
Added Streamlit to stack
Aug 2026
Added SQL to stack
Aug 2026
Added Snowflake to stack
Aug 2026
Added Amazon Redshift to stack
Aug 2026
Added Kubernetes to stack
Aug 2026
Added Rest API to stack
Aug 2026
Added Prefect to stack
Aug 2026
Jobs
$180k – $320k per year • Equity • Remote/Hybrid • 5+ years exp • New York
Python
Fine-tuning
LLM
Multimodal AI
Reinforcement Learning
AI Agents
Function Calling
Snorkel
Apply
$180k – $320k per year • Equity • Remote/Hybrid • 5+ years exp • New York
Python
Data Augmentation
Fine-tuning
LLM
Reinforcement Learning
Synthetic Data
AI Agents
Human-in-the-Loop
Snorkel
DevOps
AWS
Azure
Docker
GCP
Apply
$180k – $320k per year • Equity • Remote/Hybrid • 5+ years exp • New York
Python
SQL
LLM
Human-in-the-Loop
Snorkel
Apply
$172k – $300k per year • Equity • Remote • 3+ years exp • New York
Python
FastAPI
Mypy
Databases
Chroma
FAISS
Weaviate
AI/ML
CrewAI
Fine-tuning
LangGraph
LlamaIndex
LLM
Prompt Engineering
PyTorch
RAG
Ray
Scikit-learn
Spark
Transformers
LangChain
Hugging Face
Snorkel
AI Agents
QA
Pytest
Apply
$190k – $300k per year • Equity • Remote • Bachelor's Degree • San Francisco
Python
Fine-tuning
LLM
Prompt Engineering
RAG
Scikit-learn
Spark
Snorkel
AI Agents
Apply
$170k – $300k per year • Equity • In office • San Francisco
Snorkel
Apply
≈ $212k – $404k per year (Estimated) • Remote/Hybrid • New York
LLM
Snorkel
Apply
≈ $181k – $395k per year (Estimated) • Remote/Hybrid • PhD • New York
Python
LLM
Multimodal AI
NLP
NumPy
Pandas
PyTorch
Scikit-learn
Synthetic Data
TensorFlow
Snorkel
TPU
DevOps
AWS
GCP
Web3
Rollup
Apply
≈ $177k – $387k per year (Estimated) • Remote/Hybrid • PhD • New York
LLM
NLP
Snorkel
Apply
≈ $96k – $259k per year (Estimated) • Remote/Hybrid • 4+ years exp • New York
JavaScript
Node JS
PowerShell
Python
Claude
LLM
Prompt Engineering
Anthropic
Model Context Protocol
OpenAI
Snorkel
Frontend
GraphQL
DevOps
Azure
CI/CD
Terraform
Cybersecurity
Auth0
Crowdstrike
ISO 27001
Least Privilege
Okta
SOC 2
Zero Trust
Management
Google Workspace
Jira
Notion
Slack
Zapier
Apply
≈ $152k – $324k per year (Estimated) • Remote/Hybrid • 5+ years exp • New York
LLM
Reinforcement Learning
Synthetic Data
AI Agents
Human-in-the-Loop
Recommender Systems
Snorkel
DevOps
Amazon ECS
Apply
≈ $148k – $315k per year (Estimated) • Remote/Hybrid • Full-Time • 7+ years exp • New York
Claude
Claude Code
Cursor
LLM
Reinforcement Learning
Synthetic Data
Human-in-the-Loop
Snorkel
DevOps
CI/CD
Terraform
Cybersecurity
Auth0
FedRAMP
GDPR
SOC 2
Apply
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