About the role

Senior Machine Learning Engineer enhancing real-time AI safety solutions at Gray Swan AI. Lead development of scalable machine learning models and ensure robustness against adversarial threats.

Responsibilities

Lead 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.

Bachelor’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.
6+ 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.