Deep Learning Engineer

We are seeking a skilled and innovative Deep Learning Engineer to join our AI/ML team. As a Deep Learning Engineer, you will develop, train, and deploy computer vision models that solve complex visual problems. You will work on cutting-edge technology involving image processing, object detection, and video analysis, collaborating with cross-functional teams to create impactful real-world applications.

Role: Data Scientist / Deep Learning Engineer

Location: Pune

General Summary Of The Role

Develop and optimize computer vision models for object detection (YOLO, Faster R-CNN,

SSD) and image classification (ResNet, MobileNet, EfficientNet, ViTs).

Work with OCR technologies (Tesseract, EasyOCR, CRNN, TrOCR) for text extraction

from images.

Work with PyTorch, TensorFlow, OpenCV for deep learning and image processing.
Implement sequence-based models (RNNs, LSTMs, GRUs) for vision tasks.
Optimize software for real-time performance on multiple platforms.
Implement and deploy AI models via Flask/FastAPI and integrate with SQL/NoSQL

databases.

Use Git/GitHub for version control and team collaboration.
Apply ML algorithms (regression, decision trees, clustering) as needed.
Review code, mentor team members, and enhance model efficiency.
Stay updated with advancements in deep learning and multimodal AI.

Required Skills & Qualifications

Python proficiency for AI development.
Experience with PyTorch, TensorFlow, and OpenCV.
Knowledge of object detection (YOLO, Faster R-CNN, SSD) and image classification

(ResNet, MobileNet, EfficientNet, ViTs).

Experience with OCR technologies (Tesseract, EasyOCR, CRNN, TrOCR).
Experience with RNNs, LSTMs, GRUs for sequence-based tasks.
Experience with Generative Adversarial Networks (GANs) and Diffusion Models for image

generation.

Familiarity with REST APIs (Flask/FastAPI) and SQL/NoSQL databases.
Strong problem-solving and real-time AI optimization skills.
Experience with Git/GitHub for version control.
Knowledge of Docker, Kubernetes, and model deployment at scale on serverless and onprem platforms.
Understanding of vector databases (FAISS, Milvus).

Preferred Qualifications

Experience with cloud platforms (AWS, GCP, Azure).
Experience with Vision Transformers (ViTs) and Generative AI (GANs, Stable Diffusion,

LMMs).

Familiarity with Frontend Technologies.

Skills: computer vision,faster r-cnn,diffusion models,resnet,efficientnet,deep learning,python,ssd,github,crnn,git,fastapi,mobilenet,docker,kubernetes,rnns,azure,flask,gcp,models,platforms,opencv,tesseract,vits,databases,aws,classification,lstms,tensorflow,nosql,sql,yolo,learning,grus,pytorch,easyocr,generative adversarial networks (gans),milvus,trocr,faiss,diffusion

Deep Learning Engineer

Key Skills

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