Job Description
About 10a Labs : 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely. About the Role: We are seeking a Machine Learning Engineer (3–5+ years of experience) to help design, build, evaluate, and deploy advanced machine learning systems across a range of safety, security, and intelligence applications. This role spans the full ML lifecycle, from dataset development and experimentation to model training, evaluation, deployment, and monitoring. You will work both independently and collaboratively across projects involving multimodal classification systems, frontier model evaluations, model distillation research, and agentic workflows. The ideal candidate combines strong engineering fundamentals with a research mindset and enjoys tackling ambiguous, high-impact problems at the frontier of AI. You will collaborate closely with researchers, software engineers, red teamers, and subject-matter experts to develop production-ready systems that support leading AI organizations and technology companies. Responsibilities may include: Design, train, evaluate, and deploy machine learning models across text, image, audio, and multimodal domains. Develop and improve classification systems for safety, security, abuse detection, and intelligence applications. Conduct experiments to benchmark, evaluate, and compare AI models, including large language models and multimodal systems. Contribute to model distillation, optimization, and fine-tuning efforts to improve performance, efficiency, and deployability. Design evaluation pipelines, metrics, and testing frameworks to measure model capabilities, reliability, and safety. Build agentic systems and automated workflows for evaluation, red teaming, researc
