Senior Data Scientist - Cybersecurity

Accountabilities:

• Build, curate, clean, and maintain high-quality datasets for NLP and AI security applications, including safe and unsafe prompts, sensitive-data exposure scenarios, and adversarial examples.
• Generate and augment synthetic datasets using large language models to address edge cases and improve model robustness.
• Train, fine-tune, adapt, and evaluate NLP and transformer-based models for real-time risk detection and classification.
• Develop and improve custom classification and Named Entity Recognition (NER) models for identifying sensitive or relevant information.
• Design evaluation pipelines, benchmarks, and experiments to measure model accuracy, quality, reliability, false-positive rates, and overall performance.
• Experiment with different modeling approaches and continuously improve solutions as new use cases and AI-related security threats emerge.
• Optimize models and inference workflows for production environments where low latency and computational efficiency are critical.
• Analyze datasets and model performance to identify gaps, edge cases, failure patterns, and opportunities for improvement.
• Collaborate with AI and engineering teams to transition models and experiments from research into reliable production solutions.
• Contribute to practical AI/ML workflows, technical documentation, evaluation practices, and engineering best practices.

Requirements:

• 4+ years of professional experience as a Data Scientist, Machine Learning Engineer, or in a closely related role.
• Strong hands-on experience with Natural Language Processing (NLP), transformer-based models, and modern language-model architectures.
• Strong programming skills in Python.
• Experience with machine learning and deep learning frameworks such as PyTorch, TensorFlow, or comparable technologies.
• Practical experience with machine learning libraries and ecosystems such as Hugging Face and scikit-learn.
• Hands-on experience training, fine-tuning, or adapting machine learning models for real-world applications.
• Experience with NER, tokenization, text classification, or other relevant NLP techniques.
• Strong data preparation and analysis skills using Pandas or similar tools.
• Experience designing model evaluations, benchmarks, and experiments to assess model quality and reliability.
• Understanding of model performance optimization and inference optimization techniques.
• Familiarity with AI security concepts, including prompt injection, sensitive-data or PII exposure, adversarial inputs, and data privacy.
• Strong analytical and problem-solving skills, with the ability to investigate ambiguous machine learning problems independently.
• Ability to collaborate effectively with AI and engineering teams while maintaining a practical, production-oriented mindset.

Benefits:

• 100% remote work, allowing you to work from the location where you are most productive.
• Competitive compensation paid in USD.
• Paid time off to support rest, wellbeing, and work-life balance.
• Flexible autonomy to manage your working time based on results and deliverables.
• Opportunity to work on innovative, high-impact AI and cybersecurity projects for leading U.S. companies.
• Hands-on exposure to NLP, transformer models, LLMs, AI security, model evaluation, and production machine learning.
• Opportunity to work on evolving AI security challenges involving prompt injection, sensitive-data protection, adversarial inputs, and risk detection.
• Collaboration with experienced technical professionals across a diverse, global network.
• Multicultural and distributed working environment spanning Latin America and other international markets.
• Opportunity to collaborate with senior technology professionals and expand your technical and professional network.