Overview

As a Senior Machine Learning Engineer at Dow Jones, you will own the end-to-end ML lifecycle with a strong emphasis on LLMOps. You will build and deploy ML and agent-based solutions that scale across platforms, ensuring robust monitoring and reliable production performance. You'll collaborate with data scientists, engineers, and product teams to advance data-driven products for readers and users.

This role offers the chance to shape ML infrastructure and accelerate innovation in a dynamic media-tech environment.

Compensaciones / Incentivos Comprehensive Healthcare Plans

30 days of holidays/year

Remote work possibilities (3 months/year)

Meal benefit with Pluxee

Retirement plans with employer match

Life insurance and wellbeing resources (e.g., Spring Health)

Responsabilidades Own end-to-end ML model development, optimization and deployment.

Develop and manage LLM-based solutions, including semantic layer, fine-tuning, evaluation, deployment strategies, and agent/multi-agent systems.

Ensure scalability, efficiency, and reliability of ML pipelines.

Design robust model monitoring and retraining strategies.

Optimize model inference and performance for production environments.

Collaborate with data scientists, engineers, and product teams to integrate ML solutions.





Improve experimentation frameworks, model versioning, and A/B testing strategies.

Uphold best practices in MLOps, including automation, reproducibility, and CI/CD for ML.

Contribute to architectural decisions and improve ML infrastructure.

Mentor and provide technical guidance to junior ML engineers.

Requisitos principales Bachelors degree in Computer Science, Statistics, Mathematics, or related quantitative field

2-4 years of professional ML experience with models deployed in production

Strong experience with LLMOps, fine-tuning frameworks, prompt engineering, and lifecycle management of LLMs; experience with agent and multi-agent systems

Advanced hands-on experience with cloud-based data warehouse solutions; Snowflake preferred

Proficiency in Python and SQL; experience with TensorFlow, PyTorch

Knowledge of Scikit-learn, Pandas, NumPy

Experience building ML/MLOps pipelines using MLflow or Airflow

Experience with cloud platforms (AWS, GCP, Azure) and big data frameworks like Spark or Dask (preferred)

Collaborative mindset

Strong communication

Mentorship and coaching

LLMOps

Fine-tuning frameworks

Prompt engineering

📌 Senior Machine Learning Engineer (Barcelona)
🏢 Dow Jones u0026
📍 Barcelona