Senior MLOps Engineer: Build Scalable AI Platforms

LexisNexis Risk Solutions; Ciudad de México; Híbrido; MXN 900.000 - 1.300.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Private Medical

Dental and Vision Plan

Vacation Bonus

Learning & Development

Employee Assistance Program

Descripción de la vacante

Elsevier in Mexico City (Hybrid) is seeking a Senior MLOps Engineer to bridge data science and engineering for scalable AI platforms in research and healthcare workflows.

You will automate ML pipelines, maintain model registries, and implement CI/CD across AWS, Azure, and Databricks. The role emphasizes reliability, governance, and collaboration with product managers and data scientists to turn NLP/GenAI experiments into production services.

Formación

• 3–5+ years in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production.
• Strong Python, Java, and/or Scala engineering.
• Experience with statistical analysis, machine learning theory and natural language processing.
• Hands-on‑ experience with major cloud vendor solutions (AWS, Azure and/or Google).
• Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr/ Neo4j).
• Experience in evaluating LLM models.
• Background with scholarly publishing workflows, bibliometrics, or citation graphs.
• A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics.
• Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark.
• Experience with large scale data processing systems, e.g., Spark.

Responsabilidades

• Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, OpenAI).
• Maintain and version model registries and artifact stores to ensure reproducibility and governance.
• Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment.
• Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML.
• End-to-end custom SageMaker pipelines for recommendation systems.
• Design and implement the engineering components of GAR+RAG systems and manage prompt libraries, guardrails and structured output for LLMs.

Conocimientos

Python

Java/Scala

Cloud platforms

Elasticsearch/OpenSearch Solr

LLM evaluation

Herramientas

Spark

PyTorch

TensorFlow

PySpark

MLflow

SageMaker

Descripción del empleo

Elsevier in Mexico City (Hybrid) is seeking a Senior MLOps Engineer to bridge data science and engineering for scalable AI platforms in research and healthcare workflows.

You will automate ML pipelines, maintain model registries, and implement CI/CD across AWS, Azure, and Databricks. The role emphasizes reliability, governance, and collaboration with product managers and data scientists to turn NLP/GenAI experiments into production services.