Teams at Archer Aviation

Design, implement, and evaluate machine learning and deep learning algorithms for autonomy, trajectory prediction, and perception. Develop predictive and decision-making models, conduct experiments in simulated or dynamic environments, and build scalable research tools. Collaborate on research prototypes involving agent behavior, environmental understanding, and generative AI. Communicate findings to leadership and help transition validated research systems into production.

Design, implement, and evaluate novel machine learning and deep learning algorithms, develop scalable research tools, benchmark emerging techniques, and transition research prototypes into production AI systems. The role requires collaboration with research engineers, experimentation across data, architectures, training, evaluation, and deployment, and communication of findings to leadership. Focus areas include transformers, multimodal foundation models, diffusion policies, fine-tuning, distillation, mixture-of-experts, and potentially reinforcement, self-supervised, imitation learning, and robotic VLA models.

Leads incident detection, response, containment, eradication, recovery, threat hunting, digital forensics, SIEM/SOAR engineering, and MSSP coordination. Develops detection rules, response playbooks, automation workflows, compliance audit processes, and incident documentation. Manages endpoint detection policies, threat intelligence, tabletop exercises, and IR program strategy while communicating risk and incident findings to technical teams, executives, legal, HR, and regulatory stakeholders.