Experteer Overview
In this Senior ML Engineer role, you own the lifecycle of ML and MLOps, with a focus on LLMOps, to deliver production-ready models and intelligent tools. You will work within the Technology team to advance ML-enabled experiences for readers and users, collaborating with data scientists, engineers, and product teams. You drive scalable ML pipelines, monitoring, and retraining strategies to maintain reliable, high-performance AI solutions. This is a chance to shape how data-driven products are built and deployed at scale. You will mentor junior engineers and influence architectural decisions.

Compensaciones / Ventajas
• Develop and manage LLM-based solutions including semantic layer development, fine-tuning, evaluation, deployment, and agent/multi-agent systems
• Own end-to-end ML model development, optimization, and deployment
• Ensure scalability, efficiency, and reliability of ML pipelines
• Design and implement robust model monitoring and retraining strategies
• Optimize model inference and performance in 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 MLOps best practices: automation,



reproducibility, and CI/CD for ML
• Contribute to architectural decisions and ML infrastructure improvements
• Mentor and provide technical guidance to junior ML engineers

Responsabilidades
• Bachelor in Computer Science
• 2-4 years of ML experience with production deployments
• Strong experience with LLMOps including fine-tuning frameworks and prompt engineering
• Experience in development of agent and multi-agent systems
• Advanced hands-on experience with cloud-based data warehousing; Snowflake preferred
• Proficiency in Python and SQL; deep experience with TensorFlow or PyTorch
• Knowledge of libraries such as Scikit-learn, Pandas, and NumPy
• Experience building ML pipelines with MLflow or Airflow
• Familiarity with cloud platforms (AWS, GCP, Azure) and big data frameworks like Spark or Dask

Requisitos principales
• Comprehensive Healthcare Plans for you and your family
• Extra paid Time Off (30 days of holidays/year)
• Remote work options (3 months/year, plus 1 week per quarter)
• Meal benefit with Pluxee
• Retirement Plans (employer contributions)
• Life insurance and wellbeing resources

📌 Senior Machine Learning Engineer (Barcelona)
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📍 Barcelona