Gray Swan AI - Machine Learning Engineer

• Education • Education • Bachelor’s degree in Computer Science, Machine Learning, Engineering, or a related technical field is required. • Experience in building and deploying machine learning models and systems. • Demonstrated expertise in designing, training, and deploying deep learning models with frameworks like PyTorch. • Strong programming experience in Python and C++ (preferred) • Practical experience developing scalable machine learning pipelines and integrating them with cloud infrastructure (e.g., AWS, GCP, Azure). • Experience conducting ML research, including building research prototype systems, experiment design, empirical analysis of results, and communicating results via publications. • Good to have: experience with modern ML methods such as LLMs (training, finetuning, and/or analyzing), synthetic data generation pipelines, and AI safety or security work. • In-depth knowledge of neural network architectures, including sequence models, transformers, and other state-of-the-art approaches. • Strong algorithmic problem-solving skills and comprehensive knowledge of ML theory and optimization techniques. • Proficiency in data preprocessing, transformation, and handling large-scale, multi-modal datasets. • Experience with AI safety practices such as model validation, robustness testing, and continuous monitoring for safety and security incidents throughout deployment. • Experience 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. • research and engineering • 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. • 😇 Reference checks. We’ll reach out to 3-5 references that you provide. • 📃 Offer. If it’s mutual, we move fast.