[Hiring] Senior Data Scientist @Truelogic

Role Description

We are seeking a Senior Data Scientist to join the core AI team and work hands-on across data curation, model development, evaluation, and optimization. In this role, you will help build and improve NLP models that identify potential risks in AI interactions, including sensitive-data exposure, unsafe content, and adversarial or malicious prompts. You will work with modern transformer-based models and large language model technologies while developing high-quality datasets and evaluation processes that support reliable, low-latency AI security solutions. The ideal candidate combines strong hands-on experience in NLP, transformers, model training, and data curation with a practical approach to experimentation and production machine learning.

Responsibilities

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

Qualifications

• 4+ years of professional experience as a Data Scientist, Machine Learning Engineer, or in a closely related role.
• Strong hands-on experience with 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 similar.
• Experience with 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 working with NER, tokenization, text classification, or other 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 and inference optimization techniques.
• Familiarity with AI security concepts such as prompt injection, sensitive-data/PII exposure, adversarial inputs, and data privacy.
• Strong problem-solving skills and the ability to work independently on ambiguous ML problems.

Benefits

• 100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection.
• Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings.
• Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed.
• Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock.
• Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies.

Company Description

A growing technology company focused on helping organizations safely adopt and manage artificial intelligence at scale. Its platform helps enterprises monitor AI interactions, protect sensitive information, and apply security and governance controls across modern AI applications, including large language models and AI-powered agents.