Machine Learning Developer

Overview In this role you will advance algorithms and architectures for autonomous and semi-autonomous vehicles, applying ML and modeling to real-time decision support and collision avoidance. You will collaborate with a cross-disciplinary team to prototype deployable solutions and publish results. You will help scale and validate safety-critical systems for the transport domain, with a focus on advancing autonomous air mobility and resilient supply chains. This is a mission-driven opportunity to shape next-generation intelligent transportation technologies. Compensation / Benefits Comprehensive health, dental, and vision plansMIT-funded pension Matching 401KPaid leave (vacation, sick, parental, military)Tuition reimbursement and continuing education Mentorship programs Responsibilities Develop algorithms and system architectures for autonomous and semi-autonomous vehicles Create and validate advanced decision support systems and containment for semi-autonomous operations Lead applied R&D programs in transportation; formulate new approaches to challenges Publish research results in conferences/journals and disseminate findings to broad audiences Analyze operational problems and translate them into deployable solutions Key requirements PhD in engineering, physics, Mathematics, or computer science or Master with 4 years relevant experience Experience with state-of-the-art machine learning approaches and architectures Experience developing algorithms and architectures for autonomous systems Experience with reinforcement learning Publication record in conferences/journals Python programming experience Strong collaboration and interpersonal skills Ability to distill and communicate concepts/results to diverse audiencescollaborationclear communicationleadership potentialstate-of-the-art machine learningreinforcement learningalgorithm development for autonomous systems