AI Scientist (LATAM)
Blockchain intelligence company providing tools to detect, investigate, and manage crypto-related fraud, financial crime, and compliance for institutions and government agencies.
Funding history
Investors
About TRM Labs
TRM Labs provides blockchain intelligence for investigations and compliance, offering products such as forensics, wallet screening, entity screening, transaction monitoring, and APIs. It serves financial institutions, crypto businesses, and public sector agencies to trace funds, assess risk, and build cases across digital assets.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will join a new AI Research team to build the models and agents behind the intelligence in TRM's products. You'll train ML models on blockchain data, including foundation models, and take them from research to production. You'll build AI agents, fine-tune LLMs where helpful, and find new ways to generate net new intelligence across network, on-chain and protocol layers. You'll ship production-quality code with rigorous evaluation and work on ambitious, high-impact projects with fast turnaround for customers.
Requirements
- Quantitative background (Computer Science, Statistics, Engineering, Mathematics, Physics)
- Strong machine learning foundations
- Problem-solving mindset
- 5+ years of hands-on machine learning experience
- Strong Python, SQL and AI-assisted coding tools (Cursor, Claude Code)
- Experience with distributed data systems (Spark, BigQuery, Airflow) and shipping production ML code
- Strong async and technical communication in English
- Ability to work independently in a remote environment
- At least 4-hour overlap with PST business hours
Responsibilities
- Train ML models on blockchain data, including foundation models, and take them from research to production
- Build AI agents and fine-tune LLMs where helpful
- Generate net new intelligence using patterns across Network, On-chain and Protocol layers
- Ship production-quality code including ML models, agents and data pipelines with rigorous evaluation
- Take on ambitious high-impact projects and deliver measurable outcomes
- Deliver fast-turnaround attribution insights for key customers
Hiring Process
Recruiter intro, hiring manager interview, first round (1–2 interviews), final round hands-on case study (panel), references, then offer.
