Experteer Overview

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In this role you will own the end-to-end ML lifecycle with a strong emphasis on LLMOps, building and scaling AI-powered solutions for Dow Jones. You will collaborate with data scientists, engineers and product teams to deliver production-ready models and robust ML pipelines. The role blends hands-on work with strategic thinking to drive innovative ML infrastructure and tooling.

You will mentor peers and influence architectural decisions, enabling impactful, data-driven products for readers and users.

Compensaciones / Incentivos

- Own end-to-end ML model development, optimization and deployment
- Develop and manage LLM-based solutions including semantic layer, fine-tuning, evaluation and deployment
- Design robust model monitoring and retraining strategies
- Improve ML experimentation frameworks, versioning and A/B testing
- Ensure scalable, efficient ML pipelines and CI/CD for ML
- Collaborate with data scientists, engineers and product teams to integrate ML solutions




- Mentor and provide guidance to junior ML engineers
- Contribute to ML infrastructure and architectural decisions

Responsabilidades

- Bachelor in Computer Science, Statistics, Mathematics, or a related quantitative field; Master’s or PhD is a strong plus
- 2-4 years of professional ML experience with production deployments
- Strong experience with LLMOps including fine-tuning frameworks and prompt engineering
- Hands-on experience with cloud-based data warehouses; Snowflake preferred
- Proficiency in Python xugodme and SQL; experience with TensorFlow or PyTorch
- Knowledge of Scikit-learn, Pandas and NumPy
- Experience building ML/Ops pipelines with MLflow or Airflow
- Experience with AWS, GCP or Azure and large-scale data processing with Spark or Dask

Requisitos principales

- Comprehensive Healthcare Plans
- Extra paid Time Off (30 holidays/year)
- Remote work options (3 months/year)
- Meal benefit with Pluxee
- Retirement plans with employer match
- Life insurance and wellbeing resources

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