AI Research Scientist- Multimodal Foundational Models

Requirements

• Ph.D. in Computer Science, Electrical Engineering, Information Technology or a related discipline OR Masters degree with 2-3 years of preferred professional experience
• Expertise with Time Series FMs (beyond the time series task of forecasting)
• In-depth experience in signal processing for sensor data and their integration with deep-learning methods
• Proficiency in Python, PyTorch (including libraries such as torchaudio, torchvision, torchmetrics), familiarity with PyTorch Lightning
• A strong publication record in relevant venues such as ICASSP, NeurIPS, InterSpeech, ICML, ICLR, KDD, ICRA, CVPR, ICCV, ECCV or equivalent contributions to the field such as patents or significant open-source projects
• Strong interpersonal, communication, and teamwork capabilities
• 3+ years of experience in industrial research
• Experience with one or more of the following areas: data-centric AI, synthetic data generation, agentic AI
• Proficiency with version control systems (Git), integrated development environment (VSCode or PyCharm) and experience with experiment tracking tools (MLFlow)
• Familiarity with high-performance computing systems and job schedulers (Slurm, LSF)
• Hands-on experience in product development in the above-mentioned areas for consumer/enterprise markets
• Experience leading projects with small teams, demonstrating the ability to mentor junior researchers and interns, manage project timelines, and deliver results within time constraints
• Equal Opportunity Employer, including disability / veterans
• *Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.
• #LI-JM1

Benefits

Additional Information

Job Responsibilites: Develop and lead research of AI projects that label, predict, classify, cluster, describe and fuse multi-sensor data (including acoustic, telemetry timeseries signals, vibration, radar, lidar, image, Wi-Fi, and ultrasound data), to improve / enable advance driver assistance system (ADAS) functionality in vehicles and AI functionalities in other Bosch products. Architect, design and validate multi-modal deep learning and Timeseries Foundation Models (TSFM) to work with multivariate time series signals. Integrate and extend timeseries models to leverage information from other auxiliary modalities such as videos and images to enhance context understanding. Offer expert insights to the management team in relevant technology sectors, aiding in strategic planning, R&D trajectory, and investment decisions. Stay abreast of the latest technological innovations, document and disseminate research findings through high-caliber publications and/or patent submissions.

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