About Gray SwanGray Swan protects organizations from emerging AI security threats. We build real-time threat detection, automated validation, and adaptive defenses for AI labs and enterprises. We’re a team of ~25 people, well-funded, and growing fast.The RoleAs a Senior Machine Learning Engineer at Gray Swan AI, you will play a pivotal role in shaping the future of AI safety solutions.Research at Gray Swan AI is tightly tied to real-world impact. AI security is not a solved problem, and this role is a mix of applied research and system building: developing new approaches to adversarial testing, model evaluation, and robust inference that directly inform how secure AI systems are deployed in practice.You will work at the boundary between research and production, translating novel ideas into scalable AI systems that withstand adversarial pressure.Your expertise in state-of-the-art deep learning architectures, distributed systems, and parallel computing will enable you to tackle complex challenges associated with resource-intensive models. You will be responsible for advancing our methodologies for controlling, monitoring, and analyzing these models, ensuring they meet the rigorous demands of production environments.Join us at Gray Swan AI to leverage your deep technical knowledge and leadership skills while making a significant impact in the field of AI safety!What You’ll DoLead the design, development, and deployment of advanced machine learning models to enhance system performance and scalability.Tackle complex challenges associated with resource-intensive models using distributed systems and parallel computing.Advance methodologies for controlling, monitoring, and analyzing machine learning models in production environments.Develop new approaches to adversarial testing, model evaluation, and robust inference.Translate research ideas into scalable AI systems deployed in real-world, adversarial settings.Mentor junior engineers and drive innovation within the team.Work closely with cross-functional teams to ensure research outcomes inform production systems.Who You AreEducationBachelor’s degree in Computer Science, Machine Learning, Engineering, or a related technical field is required.A Master’s or PhD in a relevant technical field is strongly preferred, especially with a focus on machine learning and AI safety.Experience6+ years of hands-on experience in building and deploying machine learning models and systems.Experience with modern ML methods such as LLMs (training, finetuning, and/or analyzing), synthetic data generation pipelines, and AI safety or security work.Demonstrated expertise in designing, training, and deploying deep learning models with frameworks like PyTorch.6+ years of experience programming 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.Core Technical SkillsIn-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 algorithms.Proficiency in data preprocessing, transformation, and handling large-scale, multi-modal datasets.Bonus Points If You HaveTechnical leadership experience, including leading project teams or mentoring junior engineers.Experience with AI safety practices such as model validation, robustness testing, and continuous monitoring for safety and security incidents throughout deployment.Familiarity with AI safety and security assessments and adversarial testing.Hands-on experience working in collaborative, cross-functional environments with data scientists, software engineers, and product managers.Strong communication skills for articulating complex technical concepts and influencing team strategies.You’ll Thrive Here IfYou 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.Compensation & BenefitsWe offer a competitive compensation package designed to reward impact and incentivize growth. Our compensation philosophy is informed by our current valuation and recent industry data.Salary: $194,650 - 277,400Equity: Competitive equity packageBenefits:401k with up to 4% matching28 days annual leave (vacation + holidays)Health, dental, and vision coverageCatered lunches (Pittsburgh office)Flexible work arrangementsVisa sponsorship available for exceptional candidates
