Gray Swan AI - Machine Learning Researcher

• Bachelor's degree in Computer Science, Machine Learning, Engineering, or a related technical field. • A Master's or PhD in a relevant technical field is strongly preferred, especially with a focus on machine learning and AI safety. • Experience building and deploying ML models and systems. • Demonstrated expertise in designing, training, and deploying deep learning models, particularly with PyTorch. • Strong Python programming skills; C++ preferred. • Experience developing scalable ML pipelines and integrating with cloud infrastructure (AWS, GCP, or Azure). • ML research experience: building research prototype systems, designing experiments, empirical analysis of results, and communicating results via publications. • Neural network architectures, including transformers, sequence models, and other state-of-the-art approaches. • Strong algorithmic problem-solving skills and knowledge of ML theory and optimization. • Data preprocessing, transformation, and handling large-scale, multi-modal datasets. • Experience with LLMs (training, fine-tuning, or analyzing), synthetic data generation, and AI safety or security work. • AI safety practices: model validation, robustness testing, and continuous monitoring for safety and security incidents. • Familiarity with AI safety and security assessments and adversarial testing. • You'll Thrive Here If • You are genuinely excited by the intersection of research and engineering, and want to both develop new AI safety ideas and see them running in real systems. • You are motivated by real-world impact and want your work to directly influence how major AI companies deploy models right now (we work with many of the leading AI labs). • You are eager to deepen your AI safety expertise by working alongside a team that includes some of the most respected and influential thinkers in the field. • You thrive in a fast-paced, dynamic startup environment where ambiguity is expected. • You bring strong collaboration and problem-solving skills, with a focus on driving meaningful, lasting impact.