AI Developer

1 week ago

bangalore, India Blue Cloud Softech Solutions Limited Full time

Job Description – AI Developer (Deep Learning, Computer Vision & Agentic AI)Location Hybrid – BangaloreAbout the RoleWe're seeking an AI Developer with strong expertise in deep learning (CNNs, RNNs, Transformers) and hands-on experience in computer vision and sequence modeling. You will drive the development of AI systems that integrate perception (vision models), reasoning (LLMs), and action (multi-agent orchestration). This role requires both research depth and production engineering rigor, with end-to-end ownership of training, scaling, deployment, and monitoring of AI systems.Key ResponsibilitiesDeep Learning (Primary Focus)Architect and train CNN/ViT models for classification, detection, segmentation, and OCR.Build and optimize RNN/LSTM/GRU models for sequence learning, speech, or timeseries forecasting.Research and implement transformer-based architectures bridging vision and language tasks.Create scalable pipelines for data ingestion, annotation, augmentation, and synthetic data generation.Agentic AI & Multi-Agent FrameworksDesign and implement multi-agent workflows using LangChain, LangGraph, CrewAI, or similar frameworks.Develop role hierarchies, state graphs, and integrations that enable autonomous vision + language workflows.Optimize agent systems for latency, cost, and reliability.LLM Fine-Tuning & Retrieval-Augmented Generation (RAG)Fine-tune open-weight LLMs using LoRA/QLoRA, PEFT, or RLHF methods.Develop RAG pipelines integrating vector databases (FAISS, Weaviate, pgvector).Combine LLM reasoning with CNN/RNN perception modules in multimodal systems.MLOps & Deployment at ScaleDevelop reproducible training workflows with PyTorch/TensorFlow and experiment tracking (W&B, MLflow).Deploy models with TorchServe, Triton, or KServe on cloud AI stacks (AWS Sagemaker, GCP Vertex, Kubernetes).Optimize inference with ONNX/TensorRT, quantization, and pruning for cloud and edge devices.Build robust APIs/micro-services (FastAPI, gRPC) and ensure CI/CD, monitoring and automated retraining.Collaboration & MentorshipTranslate business needs into scalable deep learning solutions.Mentor junior engineers in CNNs, RNNs, and production ML practices.Lead technical reviews and promote best practices across the team.Minimum QualificationsB.S./M.S. in Computer Science, Electrical Engineering, Applied Math, or related discipline.5+ years building deep learning systems with CNNs and RNNs in production.Strong Python skills and Git workflows.Proven delivery of computer vision pipelines (OCR, classification, detection).Hands-on experience with LLM fine-tuning and multimodal AI.Experience in containerization (Docker) and deployment on cloud AI platforms.Knowledge of distributed training, GPU acceleration, and inference optimization.Preferred QualificationsResearch experience in transformer architectures (ViTs, hybrid CNN-RNN Transformer models).Prior work in sequence modeling for speech or time-series data.Contributions to open-source deep learning frameworks or vision/sequence datasets.Experience with edge AI deployment and hardware optimization.

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