[All remote jobs](https://jobicy.com/jobs.md)[![TRM Labs logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/34aa038c-221.png)](https://jobicy.com/company/trm-labs.md)[TRM Labs](https://jobicy.com/company/trm-labs.md) # AI Scientist (LATAM) AI Summary TRM Labs is seeking an experienced AI Scientist to develop production machine-learning models, foundation models, and autonomous agents using blockchain intelligence data. The role combines applied ML research with production engineering, including scalable data pipelines, model evaluation, and rapid experimentation. Candidates need at least five years of hands-on ML experience, strong Python and SQL skills, and familiarity with distributed systems such as Spark, BigQuery, and Airflow. This is a high-ownership remote role for LATAM-based professionals who can overlap with Pacific Time and communicate effectively in English. The environment is mission-driven, fast-paced, and focused on fighting financial crime and security threats.[Apply for this job](#job-application)[View company](https://jobicy.com/company/trm-labs.md)ShareRemote from[LATAM](https://jobicy.com/job-region/latam.md)SalaryUndisclosedDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceOpen levelPublished13 Nov 2026Apply before13 Dec 2026Listing views40Application actions3Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. ### Build a Safer World. [TRM Labs](https://jobicy.com/company/trm-labs.md) provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. TRM’s platforms enable investigators to trace illicit activity, build cases, and construct operating pictures of threat networks. Leading agencies and businesses worldwide rely on TRM to make the world safer and more secure. TRM Labs provides AI-powered intelligence solutions, including our AI investigations platform Ardence, that help public and private sector agencies investigate and disrupt crime and global security threats. At TRM, you’ll join a mission-driven, fast-paced team made up of experts in law enforcement, data science, engineering, and financial intelligence, tackling complex global challenges daily. As an AI Scientist on our new AI Research team, you will build the models and agents behind the intelligence that powers TRM’s products. Part of that is training foundation models on blockchain data, one of our most differentiated data layers, and part is building autonomous AI agents that generate intelligence at a scale hand-built heuristics cannot reach. You’ll work on Intel Cortex and other ambitious, cross-cutting ideas, with a broad view across intelligence rather than a single risk category. This is pioneering work that does not exist elsewhere in our industry, and it directly drives customer outcomes, from seizing illicit funds to disrupting criminal networks. The impact you’ll have here: * Train ML models on blockchain data, including foundation models, and take them from research to production. * Build AI agents (and fine-tune LLMs where it helps) so the intelligence underneath TRM’s products is generated by models and agents, not only hand-built heuristics. * Find new ways to generate net new intelligence, using patterns across all intelligence layers (Network / On-chain / Protocol) that competitors can’t replicate. * Ship production-quality code: ML models, agents and data pipelines, with rigorous evaluation and scalable architecture. * Take on ambitious, high-impact bets that raise the ceiling of what our intelligence can do, and drive measurable outcomes: billions in illicit funds traced, seized, or prevented. What we’re looking for: * Quantitative background (Computer Science, Statistics, Engineering, Mathematics, Physics). Advanced degree or equivalent research experience is a plus. * Strong machine learning foundations, built over years of applied ML and/or research (modeling, evaluation, experimentation). You don’t need to have trained a foundation model or built agents before, but you need the fundamentals to do it. * Strong problem-solving mindset: gets to the root cause, leverages creativity, and thrives in ambiguity with a hypothesis-driven, iterative approach. * 5+ years of hands-on machine learning experience, with 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 communication (Loom, Slack, Notion), strong technical communication in English, and ability to own work independently in a remote environment. * Bonus: experience with LLMs, AI agents or fine-tuning; domain curiosity or prior work in blockchain, crypto, fraud, money laundering or financial crime. About the Team: * AI Research is a new team focused on ambitious, cross-cutting ideas in attribution and intelligence. * Fully remote and globally distributed. Most overlap occurs 7am–12pm PST for meetings and collaboration. * All team members must have at least 4-hour overlap with PST business hours. * You’ll work in partnership with the category pods, whose expert-built heuristics provide the high-confidence labels our models learn from. Learn about TRM Speed in this position: * Rapid Customer Impact. Deliver last-minute, high-stakes projects for key customers — turning around attribution insights in days, not weeks. * MVP to Production. Build complex algorithms with tight timeframes (1-2 sprints for MVP) and iterate based on real customer feedback. * Parallel Execution. Juggle multiple priorities across categories and stakeholders while maintaining quality and speed. ### Application Instructions If you’re interested in joining TRM, we encourage you to apply directly. Every application is reviewed by our Talent team. Before applying, review the job description carefully and highlight the experience and impact that best demonstrate the required qualifications. Please also provide thoughtful and accurate answers to the application questions, as these will be used to evaluate your skills and qualifications for the role. If you send your resume directly to someone at TRM, we can’t guarantee it will reach the appropriate hiring team. Applying directly is the best way to ensure your application will be considered. ### Interviewing with TRM Our process is designed to understand how you think, solve problems, and deliver impact, while allowing you to evaluate TRM. Most interview processes include a case study, an AI skills assessment, and a Leadership Principles interview. * Recruiter Intro: Qualifications, motivations, and alignment with the role. * Hiring Manager: Deep dive into your relevant experience, skills, and impact. * First Round: 1–2 interviews focused on the skills most critical to the role. * Final Round: Hands-on case study. This is usually a panel-style session where we go deeper into your craft, problem-solving, and alignment with TRM. * References: Former colleagues who can provide insight into your work and impact. * Offer: Congrats! Your recruiter will present the offer and compensation details. * Welcome to TRM: We’re excited to build a safer world with you! Your recruiter will share your specific interview plan and preparation guidance along the way. ### AI Fluency at TRM AI fluency is a baseline expectation at TRM. We believe AI meaningfully changes how top performers operate. We expect every team member to use AI to accelerate and reimagine their craft, not just automate surface tasks. At TRM, AI fluency means you are among the top 10 percent of operators in your function in how you apply AI to: * Accelerate repeatable workflows * Structure and solve problems * Improve output quality * Increase speed and leverage You will be evaluated on applied AI fluency during the interview process. ### Life at TRM We are building a safer world. That promise shows up in how we work every day. TRM moves FAST. We are a high-velocity, high-ownership team that expects clarity, follow-through, and impact. People who thrive here are energized by hard problems, experimentation, and continuous feedback. If something takes months elsewhere, it will ship here in days. Our work sits at the intersection of AI, national security, and fighting crime. The problems are complex, the stakes are real, and the environment evolves quickly. The pace and intensity of the work reflect the importance of the mission. As a result, the way we operate requires a high level of ownership, adaptability, collaboration, and creative problem-solving. At TRM, you should expect: * Priorities and targets to change quickly * Operating with a high degree of ambiguity * A high level of personal ownership and accountability * Close collaboration across teams and functions * Frequent, high-touch communication * Creative problem-solving and out-of-the-box thinking * A pace that rewards urgency, adaptability, and outcomes This environment is energizing for people who enjoy building, solving hard problems, and making progress in situations that are not always fully defined. It also requires thriving in ambiguity, adjusting course as new information emerges, and maintaining focus and positivity in a fast-moving and intense environment. We also recognize that this style of operating is not for everyone. If you are primarily optimizing for predictability or a consistently balanced workload, we encourage you to use the interview process to pressure-test whether this environment is truly the right fit. We want teammates who thrive here, not just survive here. If you are excited by meaningful problems, motivated by ambitious goals, and energized by working alongside mission-driven colleagues, there is a good chance you will find TRM to be an exceptional place to grow and contribute. ### Leadership Principles We hire and grow against three leadership principles. They’re the standards for how we operate, treat each other, and make decisions. * Impact-Oriented Trailblazer: We put customers first and move with speed, focus, and adaptability. We treat every plan like an experiment – test, ship, measure, and iterate quickly. * Master Craftsperson: We care deeply about our craft. We balance speed with high standards, own outcomes end‑to‑end, and invest in getting better everyday. * Inspiring Colleague: We add clarity and energy, not noise. We bring humility, candor, and a one‑team mindset — giving and receiving feedback to make the team stronger. ### Join our Mission At TRM, we care deeply about our craft. We are looking for individuals who want their work to matter, who experiment with speed and rigor, and who take pride in building a safer world for billions of people. If you’re excited by TRM’s mission but don’t check every box, we encourage you to apply — we hire for slope, judgment, and the will to learn fast. TRM is a Series C company with $220M in total funding, backed by Goldman Sachs, Bessemer, Y Combinator, Thoma Bravo, and others. Headquartered in San Francisco, TRM operates as a distributed-first company with hubs in Los Angeles, San Francisco, New York, Washington D.C., London, and Singapore. ### Privacy Policy and Additional Information By submitting your application, you agree to allow TRM Labs to process your personal information in accordance with our [Privacy Policy](https://www.trmlabs.com/policies/privacy-policy). We collect the information you provide (such as your resume, work history, and contact details) solely for the purpose of evaluating your candidacy for current and future roles at TRM. Because our hiring cycles for certain positions may span 24 to 36 months, we retain your personal information for up to 36 months from the date of your application. After that period, your data is deleted unless a different retention period is required or permitted by law. If you are located in the European Economic Area, the United Kingdom, or another jurisdiction with applicable data protection laws, you have the right to access, correct, or request deletion of your personal data at any time before that period ends. To exercise any of these rights, contact us at [privacy@trmlabs.com](mailto:privacy@trmlabs.com). To notify TRM Labs that you believe this job posting is non-compliant, please submit a report through this [form](https://docs.google.com/forms/d/e/1FAIpQLSc6e8jRCl2cQwgIzXLpIGQXtwvMQh__TcokvO2toAAkT44A6Q/viewform?usp=dialog). No response will be provided to inquiries unrelated to job posting compliance. The use of AI tools of any kind (including but not limited to notetakers, interview assistants, and real-time coaching tools such as Otter.ai, Fireflies, Fathom, Cluey, or similar) during TRM interviews is not permitted without prior approval from TRM. TRM uses its own internal tools for note-taking to ensure a consistent and confidential experience for all candidates. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this [form](https://docs.google.com/forms/d/e/1FAIpQLSevmAzPxWOYm_7kMHb9lEJlX3tpdBeHvvvNWjsI_6xhUfnXjw/viewform?usp=dialog). ### Recruitment agencies TRM Labs does not accept unsolicited agency resumes. Please do not forward resumes to TRM employees. TRM Labs is not responsible for any fees related to unsolicited resumes and will not pay fees to any third-party agency or company without a signed agreement. Show more [Apply now >](https://jobicy.com/jobs/161936-ai-scientist-latam.md) > Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a senior, technically demanding applied AI role requiring strong ML fundamentals, production engineering ability, and comfort with ambiguous research problems. The role also expects rapid delivery, independent ownership, and work on novel blockchain intelligence use cases. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$210,000US market range (per year)$170k–$260k0$286k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. The yearly cadence and USD market estimate are inferred for a senior AI Scientist role with 5+ years of machine-learning experience, production ML responsibilities, and specialized LLM and agent development work. ## Core skills Skills and capabilities most closely associated with this opportunity. [Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Foundation Models](https://jobicy.com/jobs?search_keywords=Foundation%20Models.md)[Large Language Models](https://jobicy.com/jobs?search_keywords=Large%20Language%20Models.md)[AI Agents](https://jobicy.com/jobs?search_keywords=AI%20Agents.md)[Model Evaluation](https://jobicy.com/jobs?search_keywords=Model%20Evaluation.md)[Fine-Tuning](https://jobicy.com/jobs?search_keywords=Fine-Tuning.md)[Blockchain Analytics](https://jobicy.com/jobs?search_keywords=Blockchain%20Analytics.md)[Distributed Data Systems](https://jobicy.com/jobs?search_keywords=Distributed%20Data%20Systems.md)[Apache Spark](https://jobicy.com/jobs?search_keywords=Apache%20Spark.md)[BigQuery](https://jobicy.com/jobs?search_keywords=BigQuery.md)[Apache Airflow](https://jobicy.com/jobs?search_keywords=Apache%20Airflow.md)[Production ML](https://jobicy.com/jobs?search_keywords=Production%20ML.md)[Technical Communication](https://jobicy.com/jobs?search_keywords=Technical%20Communication.md) Sample interview questionsHow would you take a machine-learning model trained on blockchain data from initial research to a reliable production deployment?I would begin by defining the target decision, labels, evaluation metrics, and baseline heuristics. I would build reproducible data pipelines, validate data quality and leakage risks, train and evaluate the model on time-aware splits, and document failure modes. For deployment, I would package the model with monitoring for performance, drift, latency, and data quality, then iterate using analyst and customer feedback. How would you evaluate an AI agent that generates investigative intelligence rather than a simple classification output? I would use task-specific evaluation sets with verified outcomes and assess factual accuracy, evidence grounding, recall of relevant entities, and the usefulness of generated investigative leads. I would include adversarial and ambiguous cases, require traceable citations to source data, and measure human-review acceptance rates. Production evaluation would also monitor safety, hallucination frequency, latency, and impact on investigator workflows. Describe how you would approach a poorly defined problem where there is limited labeled data. I would first clarify the business outcome and identify available proxy labels, expert heuristics, and high-confidence cases. I would form explicit hypotheses, establish a simple baseline, and use exploratory analysis to understand signal quality and bias. Depending on the problem, I would combine weak supervision, active learning, representation learning, or targeted expert labeling, then iterate based on measured results. What techniques would you use to make a large-scale ML pipeline reliable when working with Spark, BigQuery, and Airflow? I would design idempotent, observable pipelines with clear data contracts, partitioning strategies, retries, and backfill support. I would add automated data-quality checks, schema validation, lineage, and alerting for late or anomalous inputs. I would also version datasets and models, test pipeline components independently, and optimize expensive queries and distributed transformations using measurable performance metrics. How do you balance rapid delivery with rigorous technical standards in a high-velocity environment? I distinguish between irreversible decisions and experiments that can be safely validated quickly. For an MVP, I define the smallest measurable outcome, use simple and reliable components, and make assumptions explicit. I maintain quality through automated tests, evaluation gates, monitoring, and concise documentation, then prioritize iteration based on real customer impact rather than speculative optimization. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. 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