In this pivotal role, you will own the entire lifecycle of MLOps from optimization to deployment, with a strong focus on LLMOps
We are seeking a highly experienced and technically adept Senior Machine Learning
Engineer to join our team. In this pivotal role, you will own the entire lifecycle of MLOps
From optimization to deployment, with a strong focus on LLMOps. This position
Demands a strong blend of hands-on technical expertise, strategic thinking, and the
Ability to foster innovation within a dynamic environment
You Will:
Develop and manage LLM-based solutions, including semantic layer
Development, fine-tuning, model evaluation, deployment strategies, and the
Development of 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 robust model monitoring and retraining strategies
Optimize model inference and performance for production environments
Collaborate closely with data scientists, engineers, and product teams to
Integrate ML solutions
Improve experimentation frameworks, model versioning, and A/B testing
Strategies
Ensure best practices in MLOps, 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
Benefits
~20 weeks of parental leave
~4 weeks of paid caregiver leave




~ Up to 4 weeks of remote work per year
~1 paid volunteer day annually
~$700 caregiver reimbursement
~ Headspace emotional wellness membership
~ Financial rewards for well-being activities
~ ClassPass fitness and wellness membership

We 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
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📌 Senior Machine Learning Engineering (Barcelona)
🏢 Dow Jones
📍 Barcelona