Job Description
We are looking for a research manager (group leader) to lead a high-impact industrial AI research team working at the intersection of cutting-edge machine learning and signal processing to build multimodal sensing AI solutions (foundation models/GenAI for multimodal signals such as radar, ultrasonic, IMU, audio, vibration, RF signals among others) and enable cross-domain business applications ranging from automotive, consumer products to manufacturing and healthcare. The key responsibilities for this position are:
Technical & Research Leadership
- Work together with lab director/leadership team to define and execute the research vision and roadmap for multimodal sensor foundation models, generative AI for temporal and spatial signals, and advanced signal processing–ML hybrids
- Ensure research outcomes meet both scientific excellence and product relevance
- Lead R&D portfolio involving machine learning on heterogeneous sensors (e.g., radar, audio, RF, IMU, vision, industrial sensors), including representation learning, self-supervised learning, and multimodal fusion to improve sensing and perception capabilities in a wide range of applications from automated vehicles, intelligent consumer products to manufacturing & industrial automation
- Advance generative and probabilistic models for signals, including simulation, synthesis, forecasting, anomaly detection, and inverse problems
- Maintain a team culture of scientific/technical excellence as evidenced by high impact IPs and/or publications in top AI conferences and journals (e.g., NeurIPS, ICLR, ICML, CVPR, ICASSP)
- Collaborate with academic partners (e.g., CMU) and represent the group in the broader research community
Productization & Commercialization
- Foster entrepreneurial research, establish rigorous SW engineering practices towards translating research into production-ready artifacts
- Live by ROI mindset: mapping R&D targets to product roadmap and potential market opportunities
- Partner closely with product, engineering, and business teams to deploy AI at scale
- Balance long-term research with near- and mid-term business impact
- Support technology transfer, IP generation, and patent strategy
People & Team Leadership
- Lead, mentor, and grow a team of PhD-level researchers and senior engineers
- Manage budget/resources and secure team competency demands from internal stakeholders
- Foster a culture of scientific rigor, collaboration, inclusion, and execution excellence
- Recruit top research and engineering talent globally
- Provide technical and career mentorship to team members