Senior MLOps Engineer, TRM Labs
LLMOps
$215-230k
+ Equity
Blockchain investigations & risk management
Open for applications
Blockchain investigations & risk management
201-500 employees
Open for applications
$215-230k
+ Equity
201-500 employees
Company mission
To build a safer financial system for billions of people.
Role
Who you are
- 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
What the job involves
- The AI Engineering Team is chartered with enabling next-generation AI applications, with a special focus on Large Language Models (LLMs) and agentic systems. Our mission is to build robust pipelines, high-performance infrastructure, and operational tooling that allow AI systems to be deployed with speed, safety, and scale
- We manage petabyte-scale pipelines, serve models with millisecond-level latency, and provide the observability and governance needed to make AI production-ready
- We’re also deeply involved in evaluating and integrating cutting-edge tools in the LLM and agent space — including open-source stacks, vector databases, evaluation frameworks, and orchestration tools that unlock TRM’s ability to innovate faster than the market
- As a Senior MLOps Engineer with a focus in LLMOps, you’ll be at the core of building and scaling the technical infrastructure for AI/ML systems
- 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
- Senior Engineer: Successfully designs and documents system improvements and features for an OKR/project from the ground up. Consistently delivers efficient and reusable systems, optimizes team throughput with appropriate tradeoffs, mentors team members, and enhances cross-team collaboration through documentation and knowledge sharing
- Staff Engineer: Drives scoping and execution of one or more OKRs/projects that impact multiple teams. Partners with stakeholders to set the team vision and technical roadmaps for one or more products. Is a role model and mentor to the entire engineering organization. Ensures system health and quality with operational reviews, testing strategies, and monitoring rigor
Our take
The crypto space has become more mainstream but it is also intensely volatile and poorly regulated, with a high degree of anonymity afforded to its users. As such it has become a major source of financial fraud with $20 billion in crypto stolen in 2022 alone. TRM Lab exists to return trust to the blockchain, helping banks, government agencies and crypto companies detect and combat fraud with its blockchain intelligence solutions.
As the risk of blockchain fraud is only increasing, with the proceeds often being used for organized crime, there are a number of companies working in this space. TRM stands out with the breadth of its crypto asset coverage and the strength of its cross-chain analytics. It has partnered with the FBI and Europol to aid its investigations, and is also used by major crypto companies MoonPay and Binance.
The company has grown its revenue by almost 500% year on year since its founding in 2018, and has raised a significant amount of capital. With the funding its secured, its further developing its product and hiring additional talent. And as businesses and government agencies increasingly come to grips with fraud in the crypto space, TRM is well poised to continue its rapid growth.
Steph
Company Specialist at Welcome to the Jungle
Insights
42% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Nov 2022
$70m
SERIES B
Dec 2021
$60m
SERIES B
Total funding: $150.1m
Company benefits
- DIstributed, not distant
- Competitive compensation package
- Paid time off: 25 days of vacation and competitive holistic paid time off plans
- Parental leave & family planning: 18 weeks of paid parental leave (if employed for at least 180 days unless the home state or country required less tenure). For select eligible regions, we also offer fertility treatments via the Carrot platform
- Health coverage: Premium coverage for medical, dental, vision and life insurance
- Company retreats
- Career growth
Company HQ
SoMa, San Francisco, CA
Leadership
Esteban Castaño
(Co-Founder & CEO)Former Business Analyst at McKinsey & Company. Founded the Digital team at Generation, a high growth youth employment program, before launching TRM in 2018.
Rahul Raina
(Co-Founder & CTO)Former Senior Business Analyst at McKinsey & Company. Former Software Engineer at Amazon Web Services and Opendoor.
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