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Blue Cloud Softech - AI Developer - Deep Learning

Blue Cloud Softech - AI Developer - Deep Learning

Blue Cloud Softech Solutions LimitedBangalore
5 days ago
Job description

About the job : About the Role :

Were 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 Responsibilities 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 Frameworks :

  • Design 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 Scale :

  • Develop 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 & Mentorship :

  • Translate 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 Qualifications :

  • B.S. / M.S. in Computer Science, 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 Qualifications :

  • Research 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
  • (ref : hirist.tech)

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