- 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 xcskxlj 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 Engineer (MLOps) (Barcelona)
🏢 Dow Jones
📍 Barcelona