Senior ML Systems Engineer, LLMs

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TRM Labs

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2018

₿ Crypto

📋 Compliance

🤝 B2B

Crypto • Compliance • B2B

TRM Labs is a blockchain intelligence company that provides transaction-monitoring, forensics, and compliance solutions for businesses and public-sector organizations dealing with cryptocurrencies. Their platform and products (examples: Compliance360, Investigation360, Seizure360, Supervision360, BlockInt API, MCP, wallet screening, Know-Your-Asset) help banks, crypto firms, regulators, law enforcement, and tax authorities detect, investigate, and block illicit crypto activity, support seizures, and meet AML/CTF and supervision requirements. TRM also offers training and certification (TRM Academy) and professional services such as incident response and capacity development.

📋 Description

• Build reusable CI/CD workflows for model training, evaluation, and deployment — integrating Langfuse, GitHub Actions, and experiment tracking, etc. • Automate model versioning, approval workflows, and compliance checks across environments. • Build out a modular and scalable AI infrastructure stack — including vector databases, feature stores, model registries, and observability tooling. • Partner with engineering and data science to embed AI models and agents into real-time applications and workflows. • Continuously evaluate and integrate state-of-the-art AI tools (e.g. LangChain, LlamaIndex, vLLM, MLflow, BentoML, etc.). • Drive AI reliability and governance, enabling experimentation while ensuring compliance, security, and uptime. • Build and enhance AI/ML Model Performance • Ensure data accuracy, consistency and reliability, leading to better model training and inferencing. • Deploy infrastructure to support offline and online evaluation of LLMs and agents — including regression testing, cost monitoring, and human-in-the-loop workflows. • Enable researchers to iterate quickly by providing sandboxes, dashboards, and reproducible environments.

🎯 Requirements

• Write high-quality, maintainable software — primarily in Python, but we value engineering ability over language familiarity. • Have a strong background in scalable infrastructure, including: • Containerization and orchestration (e.g. Docker, Kubernetes) • Infrastructure-as-code and deployment (e.g. Terraform, CI/CD pipelines) • Monitoring and logging frameworks (e.g. Datadog, Prometheus, OpenTelemetry) • Understand and implement ML Ops best practices, including: • Model versioning and rollback strategies • Automated evaluation and drift detection • Scalable model and agent serving infrastructure (e.g. vLLM, Triton, BentoML) • Deploy and maintain LLM and agentic workflows in production, including: • Monitoring cost, latency, and performance • Capturing traces for analysis and debugging • Optimizing prompt/response flows with real-time data access • Demonstrate strong ownership and pragmatism, balancing infrastructure elegance with iterative delivery and measurable impact.

🏖️ Benefits

• Additionally, this role may be eligible to participate in TRM’s equity plan.