Multimodal Time-Series AI Research Scientist

Bosch USA; Sunnyvale (CA); On-site; USD 165,000 - 195,000; Full time

Job summary

Bosch USA's Research and Technology Center North America in Sunnyvale, CA, seeks a research scientist to lead AI projects and develop Foundation Model powered AIoT solutions for ADAS and other Bosch products.

The role requires deep expertise in time-series foundation models, multi-modal data, and advanced signal processing, with strong Python/PyTorch skills and a track record of publications or patents. Collaborative, cross-functional work across R&D teams is essential.

Qualifications

• Ph.D./Masters with required years in relevant field.
• Expertise with Time Series Foundation Models beyond forecasting.
• Experience in signal processing for sensor data and deep learning integration.
• Strong publication record in AI/ML venues (e.g., ICASSP/NeurIPS/ICML/CVPR).
• Excellent communication and teamwork capabilities.

Responsibilities

• Develop and lead AI research projects labeling, predicting, classifying, clustering and fusing multi-sensor data.
• Architect and validate multi-modal foundation models for time-series signals.
• Integrate TSFM with videos/images to enhance context understanding.
• Provide expert insights to management on R&D trajectory and investment decisions.
• Disseminate research findings through publications and patents.

Skills

Time Series FMs

Sensor data processing

Python

PyTorch

Git

MLFlow

VSCode

Interpersonal skills

Slurm

Education

Ph.D. in Computer Science/Electrical Engineering/Information Technology or related

Masters with 2–3 years experience

Tools

Git

VSCode

PyCharm

MLFlow

Slurm

Job description

Bosch USA's Research and Technology Center North America in Sunnyvale, CA, seeks a research scientist to lead AI projects and develop Foundation Model powered AIoT solutions for ADAS and other Bosch products.

The role requires deep expertise in time-series foundation models, multi-modal data, and advanced signal processing, with strong Python/PyTorch skills and a track record of publications or patents. Collaborative, cross-functional work across R&D teams is essential.