In this pivotal role, you will own the entire lifecycle of MLOps from optimization to deployment, with a strong focus on LLMOpsWe are seeking a highly experienced and technically adept Senior Machine LearningEngineer to join our team. In this pivotal role, you will own the entire lifecycle of MLOpsFrom optimization to deployment, with a strong focus on LLMOps. This positionDemands a strong blend of hands-on technical expertise, strategic thinking, and theAbility to foster innovation within a dynamic environmentYou Will:Develop and manage LLM-based solutions, including semantic layerDevelopment, fine-tuning, model evaluation, deployment strategies, and theDevelopment of agent and multi-agent systemsOwn end-to-end ML model development, optimization, and deploymentEnsure the scalability, efficiency, and reliability of ML pipelinesDesign and implement robust model monitoring and retraining strategiesOptimize model inference and performance for production environmentsCollaborate closely with data scientists, engineers, and product teams toIntegrate ML solutionsImprove experimentation frameworks, model versioning, and A/B testingStrategiesEnsure best practices in MLOps, including automation, reproducibility,



and CI/CDFor MLContribute to architectural decisions and improve ML infrastructureMentor and provide technical guidance to junior ML engineersBenefits20 weeks of parental leave4 weeks of paid caregiver leaveUp to 4 weeks of remote work per year1 paid volunteer day annually$700 caregiver reimbursementHeadspace emotional wellness membershipFinancial rewards for well-being activitiesClassPass fitness and wellness membershipWe are seeking a highly experienced and technically adept Senior Machine Learning Engineer to join our teamThis position Demands a strong blend of hands-on technical expertise, strategic thinking, and theSnowflake experience strongly preferredStrong experience with LLMOps, including fine-tuning frameworks, promptProficiency in Python and SQL and deep, hands-on experience with MLQuantitative field; a Master’s degree or Ph.D. is a strong plusA grasp of the broader data science toolkit, including libraries like Scikit-learn,Frameworks like TensorFlow, PyTorchExperience with cloud platforms (AWS, GCP, or Azure) and large-scale dataA Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related2-4 years of professional experience in machine learning with a strong portfolioExperience in the development of agent and multi-agent systemsPandas, and NumPyOf models deployed in a production environmentAdvanced hands-on experience with cloud-based data warehouse solutionsProcessing frameworks like Spark or Dask is preferredAirflowExperience building and maintaining MLOps pipelines using tools like MLflow, orEngineering, and managing the lifecycle of large language models, as well as
#J-18808-Ljbffr

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