Описание:

Dow Jones is a general provider of news and business information, delivering content to consumers and organizations worldwide through print, digital, mobile, and live event formats. Its portfolio includes The Wall Street Journal, Barron’s, MarketWatch, Mansion Global, Financial News, Dow Jones Risk & Compliance, and Dow Jones Newswires.
Задачи:

Develop and manage LLM-based solutions, including semantic layer development, fine-tuning, model evaluation, deployment strategies, and agent and multi-agent systems
Own end-to-end ML model development, optimization, and deployment
Ensure the scalability, efficiency, and reliability of ML pipelines
Design and implement 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
Ensure MLOps best practices, 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
Требования:

Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field
2-4 Years of professional experience in machine learning with a strong portfolio of models deployed in production
Strong experience with LLMOps, including fine-tuning frameworks, prompt engineering, and managing the lifecycle of large language models
Experience developing agent and multi-agent systems
Advanced hands-on experience with cloud-based data warehouse solutions
Proficiency in Python and SQL
Deep hands-on experience with TensorFlow and PyTorch
Knowledge of Scikit-learn, Pandas, and NumPy
Experience building and maintaining MLOps pipelines using MLflow or Airflow
Nice to have: Master’s degree or Ph.D., Snowflake experience, experience with AWS, GCP, or Azure, experience with Spark or Dask
Условия:

📌 machine learning engineer for LLM solutions (Madrid)
🏢 Enfint
📍 Madrid