Cnn jobs in India | MyJobsCatalog

Ai/ml developer - python/nlp

PuneALPHANIMBLE TECHNOLOGIES LLP

...reinforcement learning; neural networks (CNNs, RNNs, Transformers).- Prompt Engineering and Natural Language Processing (NLP) : Tokenization, embeddings, attention mechanisms, and transformer architectures (e.g., GPT, BERT).- Model Evaluation and Deployment : Experience with Docker, Kubernetes, REST APIs, and serving models [...]

Category IT & Telecommunications

30+ days ago in Hirist

Deeptek.ai - senior computer vision engineer

PuneDeepTek Medical Imaging Pvt Ltd

...and experiment with state-of-the-art CNN and transformer-based models (ViT, Swin, hybrid architectures) tailored for healthcare imaging use cases.- Drive research initiatives focused on improving model accuracy, robustness, explainability, and clinical relevance.Data Strategy & Model Robustness :- Define and guide data [...]

Category IT & Telecommunications

30+ days ago in Hirist

Senior data scientist - llm models

Remote/Anywhere in India/Multiple LocationsTUTORAC INDIA PRIVATE LIMITED

...with deep learning architectures (CNNs, RNNs, attention models).- Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).- Strong knowledge of data handling, NLP, and model deployment.- Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or equivalent.Preferred Skills :- [...]

Category Engineering & Architecture

30+ days ago in Hirist

Machine learning engineer

Pune/Navi Mumbai/Bangalore/Mohali/Anywhere in IndHNM Solutions

...Expertise in Computer Vision (CNNs, transformers, detection/classification models).- Knowledge of CI/CD for ML deployments.- Experience with version control (Git) and GPU-based training workflows.Preferred Skills :- Experience with vector databases (FAISS, Pinecone, Weaviate).- Experience with cloud ML services [...]

Category IT & Telecommunications

30+ days ago in Hirist

Custom software engineer

BengaluruAccenture

...• Deep learning fundamentals: CNNs, RNNs/LSTMs/GRUs, and modern transformers; encoder/decoder architectures and attention. • LLM inner-workings at a practical level: tokenization, context windows, inference strategies (batching, caching, quantization), fine-tuning/PEFT, and RAG. • Inference and serving techniques for [...]