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As a Machine Learning / NLP Engineer at RavenPack, you will lead the integration of state-of-the-art ML models into our high-throughput, low-latency data platform. You will design, train, and deploy NLP solutions that complement our existing infrastructure and enable a hybrid architecture. The role involves close collaboration with engineering, data, and leadership teams to drive scalable, production-grade AI capabilities for financial services.
This is a unique chance to tackle challenging problems in entity resolution, continual learning, and reliable inference at scale.
Compensaciones / Ventajas
- Design, train, and deploy NLP models to scale the data architecture
- Build integration layers for ML predictions with production systems
- Create automated feedback loops and learning pipelines for continuous improvement
- Transition models from research to production with low-latency, high-reliability requirements
- Establish evaluation benchmarks, testing harnesses, and monitoring dashboards
Responsabilidades
- Advanced NLP u0026 Deep Learning fundamentals
- Transformer xugodme architectures: training, fine-tuning, deployment
- MLOps u0026 production engineering for low-latency environments
- Evaluation frameworks, gold-standard datasets, and performance metrics
- Complex system integration with probabilistic and legacy software
- Software engineering best practices, clean code, and CI/CD for ML