
Sr. AI/ ML Engineer
2 days ago
Position: Sr. AI/ML Engineer (OCR Solutions)
Exp: 5+ years
Location: Remote
Salary: up to 40 LPA
~ Notice Period should be max. 1 month
Key Responsibilities:
- Build and improve OCR solutions capable of handling diverse languages, scripts, and complex layouts.
- Train, fine-tune, and deploy machine learning models for text recognition across multiple languages and character sets, including low-resource languages.
- Evaluate & Improve Accuracy: Implement model evaluation metrics to continuously improve the accuracy and performance of OCR systems.
- 5Scaling OCR Solutions: Design scalable OCR models that can efficiently handle large volumes of data in real-time applications. Focus on optimizing model performance for both cloud-based and edge environments.
- Collaboration: Work with cross-functional teams, including product managers, software engineers, and UX designers, to integrate OCR functionality into products.
- Deployment & Scalability: Ensure that the OCR models are scalable and optimized for deployment in production environments (cloud and edge devices). Implement and manage CI/CD pipelines for smooth deployment.
Requirements:
- Experience in AI/ML engineering with at least 3 years of experience in building OCR solutions.
- Expertise: Strong knowledge of OCR technologies, including Tesseract, EasyOCR, PaddleOCR, or custom deep learning-based OCR systems
- Languages: Experience with multiple languages and character sets (e.g., Latin, Cyrillic, Chinese, Japanese, Arabic, Devanagari, etc.)
- Deep Learning: Proficiency with machine learning frameworks like TensorFlow, PyTorch, Keras, or MXNet
- NLP Skills: Experience in natural language processing (NLP) techniques for post-processing OCR outputs.
- Programming Languages: Strong programming skills in Python and familiarity with ML libraries (scikit-learn, OpenCV, etc.).
- Proven experience in scaling AI/ML models for production environments and containerizing applications using Docker for easier deployment and scalability.
- Cloud & DevOps: Experience deploying OCR models in cloud environments (AWS, GCP, or Azure) and working with CI/CD pipelines.
Preferred Qualifications:
- Experience with low-resource or less common languages.
- Familiarity with handwriting recognition and scene text recognition.
- Knowledge of transformer-based models like Vision Transformers (ViTs) or hybrid approaches.
- Experience with Docker, Kubernetes, and container orchestration for AI/ML model deployment.
- Contributions to open-source OCR projects
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