Overview
Todas las habilidades, cualificaciones y experiencia relevantes que necesitará un candidato seleccionado se enumeran en la siguiente descripción.
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 / Ventajas
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. xqbhyrx
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
📍 Barcelona