Senior Data Engineer, Attribution Expansion

TRM Labs; Ciudad de México; Presencial; Jornada completa

Descripción de la vacante

A blockchain intelligence company is seeking a Senior MLOps Engineer to enhance AI/ML model performance and ensure data accuracy. The ideal candidate will have strong coding skills in Python and experience with data engineering practices. This role involves building low-latency pipelines and collaborating with diverse cross-functional teams to drive innovation in data processing. Join a mission-driven team committed to creating a safer financial world.

Formación

• Write high-quality code, primarily in Python.
• Experience with data stores and processing technologies.
• Ability to cleanse and convert unstructured data.

Responsabilidades

• Build and enhance AI/ML model performance.
• Ensure data accuracy and reliability for model training.
• Collaborate with teams to embed AI models into applications.

Conocimientos

Python

Data engineering

AI/ML integration

Data processing

Communication skills

Herramientas

ClickHouse

ElasticSearch

Postgres

Docker

Kubernetes

Descripción del empleo

Join to apply for the Senior MLOps Engineer role at TRM Labs

TRM Labs is a blockchain intelligence company committed to fighting crime and creating a safer world. By leveraging blockchain data, threat intelligence, and advanced analytics, our products empower governments, financial institutions, and crypto businesses to combat illicit activity 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. Whether analyzing blockchain data, developing cutting‑edge tools, or collaborating with global organizations, you’ll have the opportunity to make a meaningful and lasting impact.

Impact and Responsibilities

• Build and enhance AI/ML model performance.
• Ensure data accuracy, consistency, and reliability, leading to better model training and inference.
• Build low‑latency, high‑throughput pipelines to enable real‑time AI applications.
• Enable AI‑powered insights for quick decision‑making.
• Integrate and evaluate new AI technologies, accelerating innovation.
• Help optimize operational costs while adding value.
• Collaborate with data science, engineering, and business teams to shift focus on model building instead of data wrangling by embedding AI models into applications and platforms.

Qualifications

• Write high‑quality code. We mostly work in Python. However, languages can be learned: we care much more about your general engineering skill than knowledge of a particular language or framework.
• Versatility. Experience across the entire spectrum of data engineering, including:
• Data stores (e.g., ClickHouse, ElasticSearch, Postgres, Redis, and Neo4j)
• Data pipeline and workflow orchestration tools (e.g., Airflow, DBT, Luigi, Azkaban, Storm)
• Data processing technologies and streaming workflows (e.g., Spark, Kafka, Flink)
• Deployment and monitoring infrastructure in public cloud platforms (e.g., Docker, Terraform, Kubernetes, Datadog)
• Loading, querying and transforming large data sets
• AI and ML integration tools like MLflow, Feast, ONNX, Apache Beam
• Comfortable working with noisy, dirty, and unstructured data to cleanse, scrape and convert it into structured data.
• High degree of initiative and ownership, combined with the ability to navigate ambiguity and adapt quickly to change.
• Exceptional ability to structure problems and identify the most critical issues to prioritize.
• Ability to communicate complex ideas effectively to both technical and non‑technical audiences, verbally and in writing.
• Experience working collaboratively in a cross‑functional environment with a diverse group of people at all levels in an organization.
• Passion for building a safer financial system for billions of people.
• Interest in virtual currencies, applications, and their use in financial networks and blockchain analysis is a plus.