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Award-Winning Mental Health Support Service. UMO provides mentoring, coaching, supervision, training and technology.
Machine Learning Engineer, NLP
Location
Portugal
Posted
77 days ago
Salary
0
Seniority
Senior
Job Description
Machine Learning Engineer, NLP
UMO
• Build and deploy NLP models to analyze news, social media (Twitter/X, Discord), and Reddit to gauge market sentiment for stocks and crypto assets. • Develop systems to identify and extract entities (tickers, company names, wallet addresses, transaction IDs) from unstructured financial documents and chat logs. • Create pipelines to parse and extract data from financial statements, whitepapers, and regulatory filings (e.g., SEC filings) to assist in automated research. • Implement NLP techniques to analyze transaction metadata and communication patterns to identify potential money laundering (AML) or fraudulent payment activity. • Build or fine-tune LLMs (Large Language Models) to power specialized chatbots capable of answering complex queries about portfolio performance, crypto protocols, or trading rules. • Optimize internal search engines using semantic search and embeddings to help users find relevant financial instruments or transaction history. • Manage the full MLOps lifecycle, including data labeling for financial jargon, model training, deployment via APIs, and monitoring for "model drift" in volatile markets.
Job Requirements
- BA, Master’s or PhD in Computer Science, Data Science, or a related field with a focus on Natural Language Processing or Deep Learning.
- Advanced proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Proven experience with Transformers (BERT, RoBERTa), Large Language Models (LLMs), and vector databases (e.g., Pinecone, Milvus, or Weaviate).
- Strong experience in building data pipelines using tools like Spark, Kafka, or Airflow, and proficiency in SQL.
- Familiarity with financial terminology and the ability to handle domain-specific data challenges (e.g., interpreting ticker symbols vs. common words).
- Experience deploying models in a cloud environment (AWS, GCP, or Azure) using Docker and Kubernetes, ensuring low-latency inference for real-time trading signals.
- Ability to design robust evaluation frameworks for NLP models, moving beyond standard metrics to business-impact metrics like "signal-to-noise ratio" in trading.
- A "builder" mindset with the ability to prototype rapidly and move from a research paper to a production-ready feature in weeks, not months.
- Fluent in English with excellent documentation and cross-team coordination skills.
Benefits
- A highly competitive salary package that recognizes your expertise and contribution.
- Embrace a remote-first environment with flexible working hours, designed to support your work-life harmony.
- Annual Leave- 24 days, dedicated paid sick leave, and Public Holidays.
- Grow your skills with a dedicated learning budget and clear pathways for accelerated career development.
- Join a world-class team building a prestigious, next-generation modern money platform that is redefining the future of finance.
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