Senior Data Scientist – Cybersecurity

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

📋 Description

• Construct, curate, cleanse, and sustain datasets for Natural Language Processing (NLP) and AI security applications.

• Create and enhance synthetic datasets utilizing Large Language Models (LLMs) to address edge cases and bolster model resilience.

• Train, refine, and assess NLP and transformer-based models for real-time risk detection and classification tasks.

• Develop and enhance custom classifiers and Named Entity Recognition (NER) systems.

• Design evaluation frameworks and benchmarks to evaluate model quality, accuracy, false positives, and performance metrics.

• Experiment with various modeling techniques and continually enhance models as new use cases and AI-related threats arise.

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

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

• Analyze model performance and datasets to pinpoint 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.

• Extensive 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 such as PyTorch, TensorFlow, or equivalent.

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

• Practical experience in training, fine-tuning, or adapting machine learning models for practical applications.

• Experience working with NER, tokenization, text classification, or other NLP methodologies.

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

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

• Knowledge of model performance and inference optimization strategies.

• Awareness of AI security concepts such as prompt injection, sensitive data/PII exposure, adversarial inputs, and data privacy.

• Excellent problem-solving abilities and the capacity to work independently on ambiguous machine learning challenges.

🏝️ Benefits

• 100% Remote Work

• Highly Competitive USD Pay

• Paid Time Off

• Work with Autonomy

• Collaborate with Top American Companies

• Engagement activities

• Work-life balance

• Collaborate with a diverse, multicultural global network

• Work alongside seasoned senior professionals