Experteer Overview In this role you will own the full ML lifecycle with a focus on LLMOps, building and deploying scalable ML solutions that power editorial, product and data platforms. You will collaborate with data scientists, engineers and product teams to deliver production-grade models and intelligent tools. You’ll design robust monitoring, retraining, and optimization strategies to maintain high performance in real-world settings. This is an opportunity to shape next-generation AI capabilities at Dow Jones and influence how readers and users access information.Compensaciones / Ventajas
- Develop and manage LLM-based solutions (semantics, fine-tuning, evaluation, deployment) and multi-agent systems
- Own end-to-end ML model development, optimization and deployment
- Ensure ML pipeline scalability, efficiency and reliability
- Design robust model monitoring and retraining strategies
- Optimize model inference and production performance
- Collaborate with data scientists, engineers and product teams to integrate ML solutions
- Improve experimentation frameworks, model versioning and A/B testing
- Advance MLOps practices including automation, reproducibility and ML CI/CD
- Contribute to ML infrastructure and architectural decisionsResponsabilidades
- 2-4 years of professional ML experience with production-ready models
- Strong LLMOps experience (fine-tuning, prompt engineering, lifecycle management)
- Experience developing agent and multi-agent systems
- Advanced hands-on experience with cloud-based data warehouses; Snowflake preferred
- Proficiency in Python and SQL; deep experience with TensorFlow or PyTorch
- Knowledge of Scikit-learn, Pandas, NumPy
- Experience building MLOps pipelines with MLflow or Airflow
- Experience with cloud platforms (AWS, GCP, Azure) and large-scale data processing frameworks (Spark, Dask)Requisitos principales
- Comprehensive Healthcare Plans
- Extra paid Time Off
- Remote work possibilities
- Meal benefit with Pluxee
- Retirement Plans
- Comprehensive Insurance Plans