6 days ago
Remote, SpainSenior
Responsibilities
- Design, train, and deploy state-of-the-art NLP models within RavenPack’s high-throughput data architecture.
- Build integration layers connecting machine learning predictions with established production systems.
- Develop automated feedback loops and continuous learning mechanisms.
- Move models from research and evaluation into production while optimizing for low-latency inference and reliability.
- Create evaluation benchmarks, testing harnesses, monitoring dashboards, and performance metrics.
- Integrate probabilistic ML models with deterministic or legacy software architectures, including confidence scoring and A/B testing rollouts.
Requirements
- Deep theoretical and practical knowledge of NLP tasks such as entity extraction, text classification, and contextual understanding.
- Proven experience training, fine-tuning, and deploying transformer-based models.
- Strong experience with model optimization, batch inference, model distillation, hardware acceleration, and scalable deployment.
- Expertise in evaluation frameworks, gold-standard datasets, performance metrics, and edge-case analysis.
- Experience integrating machine learning models with deterministic or legacy software systems.
- Strong software engineering skills, including scalable code, technical documentation, and CI/CD pipelines for ML models.
- European legal working status is required.
Categories
About RavenPack
RavenPack builds NLP-driven analytics that turn unstructured content—news, filings, and social media—into machine-readable data for quantitative investors and risk teams. It sells data feeds, APIs, and a SaaS platform, including Bigdata.com, an agentic AI workspace launched in 2024 for financial research. Founded in 2003 and headquartered in Marbella, Spain, the privately held firm is used by hedge funds, banks, and asset managers.