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UMO3 months ago

Machine Learning Engineer (NLP)

Hybrid · Lisbon, Lisbon, Portugal

Type
Full Time
Level
Mid Level
Education
Masters Degree
Company size
Unknown

Job Summary

Machine Learning Engineer (NLP) responsible for building and deploying NLP models for financial sentiment analysis across stocks and crypto; develop NER systems, automated document processing pipelines, fraud/anomaly detection, and intelligent customer support using LLMs; optimize internal search/discovery with embeddings; manage full MLOps lifecycle from data labeling to deployment and monitoring for model drift; collaborate across teams to deliver production-ready features. Requires BA, Master’s or PhD in CS/Data Science with NLP/Deep Learning focus, strong Python and DL framework skills (PyTorch/TensorFlow), experience with Transformers, LLMs, vector databases; data pipelines (Spark, Kafka, Airflow), SQL; cloud deployment (AWS/GCP/Azure) with Docker/Kubernetes; familiarity with financial terminology; English communication and documentation skills; dynamic work environment with offices in Lisbon, Dubai, Kyiv, Lviv and openness to remote for the right fit.

Required Qualifications

  • 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
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UMO

Machine Learning Engineer (NLP)

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