AI Safety Researcher/Engineer

🤖 Role Description

We are looking for a highly analytical and technically skilled

AI Safety Researcher/Engineer

to help develop reliable, robust, and responsible artificial intelligence systems. 🛡️🧠 The role focuses on identifying and mitigating risks associated with AI behavior, improving model reliability, and developing practical safety techniques for advanced AI systems.

Key responsibilities include:

• 🔬 Researching methods to improve AI safety, reliability, robustness, and controllability.

• 🧠 Investigating model behavior, failure modes, vulnerabilities, and unexpected outputs.

• 🛡️ Developing and evaluating techniques for AI alignment, monitoring, evaluation, and risk mitigation.

• 🧪 Designing experiments, benchmarks, red-team evaluations, and safety tests for AI models and systems.

• 🔎 Analyzing model outputs to identify harmful, deceptive, biased, or otherwise undesirable behaviors.

• 📊 Building evaluation frameworks, metrics, datasets, and tooling to measure AI safety and performance.

• 💻 Implementing research ideas and safety mechanisms using modern machine-learning and software-engineering practices.

• 🔄 Collaborating with researchers, engineers, data scientists, policy specialists, and product teams.

• 📚 Reviewing academic research and emerging developments in AI safety, alignment, interpretability, and responsible AI.

• ⚙️ Improving testing, monitoring, and deployment processes to support safer AI systems.

• 📝 Documenting research findings, methodologies, risks, experiments, and recommendations clearly.

• 🚀 Exploring emerging approaches to scalable oversight, interpretability, robustness, adversarial testing, and AI governance.

🎓 Qualifications

• ✅ Degree or relevant qualification in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Engineering, or a related field.

• 🤖 Strong understanding of machine learning, deep learning, AI systems, and model evaluation.

• 💻 Strong programming and software-engineering skills, particularly with Python and relevant ML frameworks.

• 🧠 Solid understanding of statistical reasoning, experimentation, optimization, and data analysis.

• 🔬 Familiarity with AI safety concepts such as alignment, robustness, interpretability, red teaming, adversarial evaluation, and model behavior analysis.

• 🛡️ Understanding of responsible AI, AI risk, safety principles, and ethical considerations.

• 📊 Ability to design rigorous experiments, analyze results, and draw evidence-based conclusions.

• 🔎 Strong critical-thinking and problem-solving skills with excellent attention to detail.

• 📚 Ability to understand and evaluate technical research papers and emerging AI methodologies.

• 🤝 Strong written and verbal communication skills with the ability to collaborate across multidisciplinary teams.

• 🚀 Curiosity, intellectual rigor, and a strong interest in solving challenging problems related to advanced AI safety.

• ⭐ Commitment to building AI systems that are reliable, trustworthy, beneficial, and safe for users and society.