Senior Expert â Vision-Language Models and Generative AI (GenAI)
Senior Expert â Vision-Language Models and Generative AI (GenAI)
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Job Description
Roles & Responsibilities:
Conduct deep research in:
Vision-Language and Multimodal AI for perception and semantic grounding
Cross-modal representation learning for real-world sensor fusion (camera lidar radar text)
Multimodal generative models for scene prediction intent inference or simulation
Efficient model architectures for edge deployment in automotive and factory systems
Evaluation methods for explainability alignment and safety of VLMs in mission-critical applications
Spin newer research directions and drive AI research programs for autonomous driving ADAS and Industry 4.0 applications.
Create new collaborations within and outside of Bosch in relevant domains.
Contribute to Boschs internal knowledge base open research assets and patent portfolio.
Lead internal research clusters or thematic initiatives across autonomous systems or industrial AI.
Mentor and guide research associates interns and young scientists.
Qualifications :
Educational qualification:
Ph.D. in Computer Science / Machine Learning / AI / Computer Vision or equivalent
Experience:
8 years (post PhD) in AI related to Vision and Language modalities excellent exposure and hands on research in GenAI VLMs Multimodal AI or Applied AI Research.
Mandatory/requires Skills:
Deep expertise in:
Vision-Language Models (CLIP Flamingo Kosmos BLIP GIT) and multimodal transformers
Open- and closed-source LLMs (e.g. LLaMA GPT Claude Gemini) with visual grounding extensions
Contrastive learning cross-modal fusion and structured generative outputs (e.g. scene graphs)
PyTorch HuggingFace OpenCLIP and deep learning stack for computer vision
Evaluation on ADAS/mobility benchmarks (e.g. nuScenes BDD100k) and industrial datasets
Strong track record of publications in relevant AI/ML/vision venues
Demonstrated capability to lead independent research programs
Familiarity with multi-agent architectures RLHF and goal-conditioned VLMs for autonomous agents
Preferred Skills:
Hands-on experience with:
Perception stacks for ADAS SLAM or autonomous robots
Vision pipeline tools (MMDetection Detectron2 YOLOv8) and video understanding models
Semantic segmentation depth estimation 3D vision and temporal models
Industrial datasets and tasks: defect detection visual inspection operator assistance
Lightweight or compressed VLMs for embedded hardware (e.g. in vehicle ECUs or factory edge)
Knowledge of reinforcement learning or planning in embodied AI context
Strong academic or industry research collaborations
Understanding of Bosch domains and workflows in mobility and manufacturing
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
