Generative AI & Unstructured Data ML Engineer – Hybrid

Oliver Wyman; Ciudad de México; Híbrido; MXN 900.000 - 1.300.000; Jornada completa

Descripción de la vacante

Oliver Wyman, a Marsh entity, seeks an ML Engineer – Generative AI & Unstructured Data to design, build, and operationalize AI systems transforming enterprise unstructured data into scalable, production-ready services. You will work with Data Scientists, Data Engineers, and Developers to deploy robust ML pipelines and secure APIs using cloud and ML tooling.

You will contribute to CI/CD, MLOps, and retrieval-based workflows, collaborating across teams to translate business needs into scalable

Formación

• 3+ years of professional experience in ML Engineering, Applied AI, Data Science, or related engineering roles with a focus on production systems.
• Hands-on experience building solutions using unstructured data, including NLP pipelines, document processing, OCR, text classification, embeddings, entity extraction, or semantic search.
• Proficiency in Python and SQL; experience building scalable data and ML workflows using PySpark and Databricks or similar distributed compute platforms.
• Experience developing and deploying production APIs for ML model serving using FastAPI or similar frameworks.
• Familiarity with MLOps practices including CI/CD for ML, model monitoring, automated retraining, Docker, and Git-based workflows.
• Experience working with cloud-based AI/ML platforms and enterprise deployment environments.
• Strong software engineering fundamentals, including readable code, testing, debugging, and performance optimization.

Responsabilidades

• Design and build scalable ML pipelines that ingest and process unstructured data including documents, transcripts, images, logs, and free-form text.
• Develop and maintain production-ready AI services and APIs consumed by internal applications and analytics platforms.
• Productionize machine learning and Generative AI solutions, including model packaging, containerization, deployment, versioning, and lifecycle management.
• Build and integrate Generative AI workflows such as Retrieval-Augmented Generation (RAG), embedding pipelines, semantic search, and LLM-powered APIs.
• Implement monitoring, observability, and model performance tracking to ensure reliability, scalability, and SLA compliance of deployed systems.
• Collaborate with Data Scientists to transition experimental models into stable production environments.
• Contribute to CI/CD and MLOps practices including automated testing, deployment automation, retraining workflows, and infrastructure standardization.
• Partner with cross-functional stakeholders to translate business needs into scalable AI-enabled solutions.
• Document systems and decisions clearly so teammates can understand, extend, and maintain your work.

Conocimientos

Python

SQL

PySpark

Databricks

FastAPI

MLOps

Cloud platforms

Software engineering

Herramientas

Docker

Git

LangChain

LlamaIndex

Descripción del empleo

Oliver Wyman, a Marsh entity, seeks an ML Engineer – Generative AI & Unstructured Data to design, build, and operationalize AI systems transforming enterprise unstructured data into scalable, production-ready services. You will work with Data Scientists, Data Engineers, and Developers to deploy robust ML pipelines and secure APIs using cloud and ML tooling.

You will contribute to CI/CD, MLOps, and retrieval-based workflows, collaborating across teams to translate business needs into scalable