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Senior Machine Learning NLP (Contractor)

RavenPack


Job Location:

Marbella - Spain

Monthly Salary: Not provided by the employer
Posted: 16 September 2026 (3 hours ago)
Application Deadline: 14 December 2026
Vacancies: 1 Vacancy

Job Summary

About us

At RavenPack we are at the forefront of developing the next generation of generative AI tools for the finance industry and beyond. With 23 years of experience as a leading big data analytics provider for financial services we empower our clientsincluding some of the worlds most successful hedge funds banks and asset managersto enhance returns reduce risk and increase efficiency by integrating public information into their models and workflows. Building on this expertise we are launching a new suite of GenAI and SaaS services designed specifically for financial professionals.

Join a Company that is Powering the Future of Finance with AI

RavenPack has been recognized as the Best Alternative Data Provider by WatersTechnology and has been included in this years Top 100 Next Unicorns by Viva Technology. RavenPack has launched Bigdata our Gen-AI platform tailored for finance which is already being recognized as the #1 platform for powering financial AI agents.

European legal working status is required.


Project Scope & Core Responsibilities


We are looking for an experienced Machine Learning / NLP Engineer to lead a high-impact transformational infrastructure project. You will be responsible for designing evaluating and deploying advanced machine learning models to complement and enhance our large-scale high-precision detection pipeline.

In this role you will work closely with our core engineering data and technical leadership teams to ensure the seamless integration of new ML technologies with our existing systems.

The core objective of your role is to introduce modern state-of-the-art ML approaches that run alongside our existing infrastructure to create a powerful hybrid architecture. This is a unique opportunity to tackle complex challenges in low-latency inference massive-scale entity resolution and continuous learning systems.

Note: Due to the highly proprietary nature of our systems the specific deliverables architecture and exact technologies will be discussed in detail under an NDA during your first interview.

Key Responsibilities
  • System Enhancement & Innovation: Design train and deploy state-of-the-art Natural Language Processing (NLP) models to complement and scale our existing high-throughput data architecture.

  • Architecture Integration: Build robust integration layers that allow new machine learning predictions to work seamlessly alongside our established production systems.

  • Continuous Improvement Pipelines: Develop automated feedback loops and learning mechanisms that enable our systems to adapt update and improve over time with minimal manual intervention.

  • Production Deployment & Optimization: Transition models from research/evaluation into full production optimizing complex models for strict low-latency inference and high reliability.

  • Quality & Evaluation Frameworks: Establish rigorous evaluation benchmarks automated testing harnesses and monitoring dashboards to guarantee the accuracy and stability of ML implementations.

Revised Required Skills & Experience
  • Advanced NLP & Deep Learning: Deep theoretical and practical understanding of core NLP tasks such as entity extraction text classification and contextual understanding.

  • Transformer Architectures: Proven experience training fine-tuning and deploying modern transformer-based models and encoding methods for complex text tasks.

  • MLOps & Production Engineering: Strong track record of optimizing models for low-latency environments (e.g. batch inference model distillation hardware acceleration) and deploying them at scale.

  • Evaluation & Metrics: Expertise in designing ML evaluation frameworks building gold-standard baseline datasets and tracking performance metrics to identify and resolve edge cases.

  • Complex System Integration: Experience combining probabilistic machine learning models with deterministic or legacy software architectures including confidence scoring and A/B testing rollouts.

  • Software Engineering Best Practices: Strong coding skills with a focus on writing clean scalable code creating technical documentation and maintaining robust CI/CD pipelines for ML models.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race religion colour national origin gender sexual orientation age marital status veteran status or disability status.




About Company

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RavenPack is a global leader in financial data and intelligence, helping organizations turn vast amounts of unstructured information into decision-ready insight.Since 2003, RavenPack has focused on solving one of finance’s most persistent challenges: data is abundant, but usable data ... View more

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