Shangeth Rajaa
Senior Machine Learning Scientist at Anyreach
Bengaluru, Karnataka, India
Summary
👤
Senior🎓
Top SchoolShangeth Rajaa is a Senior Machine Learning Scientist with nine years of experience building multi-modal AI systems spanning vision, speech and dialogue for startups and research labs. He has driven production and research efforts at Anyreach AI, ScoreTravel AI and Skit, specializing in multimodal LLMs, spoken-dialogue systems, RLHF/DPO and prosody-informed E2E-SLU. His background includes research roles at NTU and IBM, contributions to AutoDL collaborations, and hands-on computer vision content development for OpenCV, reflecting a mix of academic rigor and product-minded engineering. On GitHub he has practical contributions to learnopencv notebooks showcasing Faster R-CNN and Mask R-CNN inference pipelines, highlighting an applied focus on detection and segmentation. Based in Bengaluru with an MSc in Mathematics and a BE in Electrical & Electronics, he combines strong theoretical foundations with a track record of shipping applied ML solutions. Notably, he blends speech representation research with deployable multimodal LLM tooling—bridging cutting-edge research and real-world systems.
9 years of coding experience
6 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and Science
English, Tamil, Hindi
Stackoverflow
21reputation
2kreached
0answers
1question
Github Skills (13)
mask-rcnn10
faster-rcnn10
opencv10
machine-learning10
computer-vision10
deep-learning10
pytorch10
deeplearning-ai10
python9
deep-neural-networks9
object-detection8
instance-segmentation8
tensor6
Programming languages (7)
Github contributions (5)
spmallick/learnopencv
Jun 2019 - Jun 2019
Learn OpenCV : C++ and Python Examples
Role in this project:
ML Engineer
ML EngineerContributions:17 commits, 2 PRs in 7 days
Contributions summary:Shangeth's commits primarily focus on adding and modifying notebooks related to object detection and instance segmentation using pre-trained models in PyTorch. The changes include code for utilizing Faster R-CNN and Mask R-CNN models from the torchvision library. These notebooks demonstrate practical applications in computer vision. The user also added inference image examples and performed updates to the notebooks.
opencv-librarypythondeep-learningopencv3computer-vision
shangeth/shangeth.github.io
Jul 2018 - Jul 2021
Contributions:140 pushes, 1 branch in 3 years
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