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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.
Responsabilidades
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
Requisitos principales
Advanced NLP & Deep Learning fundamentals
Transformer architectures: training, fine-tuning, deployment xqbhyrx
MLOps & 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
NLP
Deep Learning
Transformers
MLOps
Production Engineering
Evaluation & Metrics