AI Research Engineer
Origin (company site, opens in a new tab)3+ yrsBengaluruOn-siteDirect career pageEst. 20–35 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop and deploy diffusion-based generative models for photorealistic simulations and defect synthesis in construction environments.
- Architect and train Vision-Language Models (VLMs) and Vision-Language Action Models connecting textual work orders, CAD plans, and sensor data to pixel-level understanding.
- Own end-to-end lifecycle of AI model development including research, prototyping, evaluation, scaling auto-annotation pipelines, optimization for edge devices, and handoff to perception & controls teams.
Minimum Requirements
- 3+ years experience in deep-learning R&D or equivalent Ph.D./M.S. in CS, EE, Robotics or related field with a strong publication record.
- Expertise in diffusion models (DDPM, LDM, ControlNet) and multimodal transformers/VLMs (CLIP, BLIP-2, LLaVA, Flamingo).
- Proven experience with large-scale active learning, pseudo-labeling, and weak supervision data workflows.
- Proficiency in Python and PyTorch (or JAX), with experience in scalable training frameworks and edge-AI runtimes (TensorRT, ONNX Runtime), CUDA/C++ performance tuning.
Ideal Candidate Profile
- Strong researcher comfortable translating mathematical and theoretical AI concepts into production-grade code and real-time systems.
- Experienced in building scalable data-centric AI pipelines suitable for complex, dynamic real-world environments like construction sites.
- Background in robotics and edge deployment environments, with ability to optimize AI models for Jetson-class devices running ROS 2.