T
Tata Consultancy Services
Vision AI Solution Architect
Skills
Google Cloud PlatformDockerPythonTesting & QAPyTorchMachine LearningAIAWSKubernetesAzure
2 months ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
24 August 2026
What they need
- Strong hands-on experience with CLIP and other contrastive embedding models, and Vision-Language Models (VLMs) for tasks such as captioning, visual QA, and grounding.
- Practical experience designing Vision RAG systems, including multimodal embeddings, vector databases, and retrieval-augmented generation patterns.
- Experience fine-tuning and adapting vision/VLM models using parameter-efficient techniques (LoRA/QLoRA) and classical CV model training/transfer learning.
- Working knowledge of hyperscaler AI/vision services across at least two of AWS, GCP, and Azure, and their trade-offs for vision workloads.
- Familiarity with edge AI deployment hardware accelerators (NVIDIA Jetson, Coral/edge TPU), model compression, quantization, and runtime optimization.
- Proficiency in Python and vision/ML frameworks (PyTorch, Hugging Face Transformers, OpenCV) and model format/runtime tooling (ONNX, TensorRT, OpenVINO).
- Understanding of containerization and orchestration (Docker, Kubernetes) for scalable vision model serving.
- Strong architectural and communication skills, with the ability to translate business needs into technical vision/GenAI solution designs.
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