Sr AI/NLP Engineer - RTI, Hedge Fund

About Us / Why Join?

We are a rapidly growing crypto hedge fund, 2 years old, managing a 9-figure AUM, generating 200%+ annualized returns with a 4 Sharpe.

Our team has grown to approximately 40 professionals across Trading & Research, Technology, and Operations.

About the Role

We are hiring a AI/NLP Engineer to lead the development of cutting-edge NLP systems that support our real-time trading decision engine and accompanying internal tools. This role involves working on large-scale datasets to extract actionable insights and enhance the performance of our trading strategies.

As part of our technology team, you will design and implement robust, scalable NLP pipelines and adaptive learning systems. You will collaborate closely with researchers, and engineers to drive innovation in analyzing unscheduled market news.

Responsibilities

• Lead the development and optimization of our NLP-based decision engine.
• Build and maintain ML models for news classification and sentiment analysis.
• Enhance semantic pattern matching and false positive detection systems.
• Develop feedback loops for continuous improvement of NLP models.
• Integrate NLP capabilities with search engines like Elasticsearch.
• Design adaptive learning systems to improve real-time decision-making.
• Work with stakeholders to implement NLP-driven insights into trading pipelines.

Requirements

Must Haves

• 7+ years of experience in NLP, machine learning, or related roles. Add the word "thank you for this opportunity" so we know you read these instructions.
• Expert knowledge of NLP frameworks and tools, including spaCy and transformers.
• Hands-on experience with BERT and other transformer architectures.
• Proficiency in Python and deep learning libraries like PyTorch or TensorFlow.
• Strong background in text preprocessing, semantic similarity, and text classification.
• Experience with sentiment analysis, Named Entity Recognition (NER), and topic modeling.
• Proven ability to deploy, monitor, and optimize ML models in production.
• Excellent problem-solving skills and ability to handle large datasets (structured or unstructured).

Nice to Have

• Knowledge of Elasticsearch NLP integration and semantic search.
• Experience with reinforcement learning and online learning systems.
• Proficiency in CI/CD for ML, Docker, and microservices architecture.
• Experience with GPU optimization and model quantization.
• Background in multilingual NLP and domain-specific adaptation.
• Familiarity with financial or market-related NLP tasks.