Blue Cloud Softech

2 weeks ago

Bengaluru, India Blue Cloud Softech Solutions Limited Full time

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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