Senior Data Scientist – Cybersecurity

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Construct, organize, cleanse, and sustain datasets for NLP and AI security applications.

• Create and enhance synthetic datasets utilizing LLMs to address edge cases and boost model robustness.

• Train, fine-tune, and assess NLP and transformer-based models for real-time risk identification and classification.

• Develop and refine custom classifiers and Named Entity Recognition (NER) models.

• Design evaluation frameworks and benchmarks to assess model quality, accuracy, false positives, and overall performance.

• Experiment with various modeling techniques and consistently enhance models as new applications and AI-related threats arise.

• Optimize models and inference processes for production environments where speed and efficiency are paramount.

• Collaborate with engineering and AI teams to transition models and experiments from research to dependable production solutions.

• Analyze model performance and datasets to uncover gaps, edge cases, and potential areas for enhancement.

• Contribute to effective AI/ML workflows, documentation, and best practices.

⛳️ Requirements

• A minimum of 4 years of professional experience as a Data Scientist, Machine Learning Engineer, or in a closely related field.

• Significant hands-on experience with NLP, transformer-based models, and contemporary language-model architectures.

• Proficient programming skills in Python.

• Experience with machine learning and deep learning frameworks, including PyTorch, TensorFlow, or similar.

• Familiarity with libraries and ecosystems such as Hugging Face and scikit-learn.

• Practical experience in training, fine-tuning, or adapting machine learning models for real-world scenarios.

• Experience in NER, tokenization, text classification, or other NLP techniques.

• Strong data preparation and analysis capabilities using Pandas or similar tools.

• Experience in designing model evaluations, benchmarks, and experiments to evaluate model quality and reliability.

• Knowledge of model performance and inference optimization techniques.

• Understanding of AI security concepts such as prompt injection, sensitive-data/PII risk, adversarial inputs, and data privacy.

• Excellent problem-solving capabilities, with the ability to work independently on ambiguous machine learning challenges.

🏝️ Benefits

• 100% Remote Work

• Highly Competitive USD Pay

• Paid Time Off

• Work with Autonomy

• Work with Top American Companies

• Engagement activities

• Work-life balance

• Collaboration with a diverse, global network

• Work alongside seasoned senior professionals