- Design, develop, and maintain robust data pipelines and workflows for AI/ML tasks.

- Perform root cause analysis (RCA) on model performance, data issues, and system failures; proactively identify and resolve bottlenecks.

- Write clean, efficient, and scalable Python code for AI/ML applications.

- Build, document, and maintain backend APIs using FastAPI to support real-time and batch inference services.

- Apply machine learning and deep learning techniques for text classification, image classification, and other predictive tasks.

- Develop and integrate NLP models for tasks such as sentiment analysis, summarization, entity recognition, and more.

- Use YOLO, OpenCV, and OCR libraries (e.g., Tesseract, EasyOCR) for computer vision applications.

- Leverage Generative AI models (e.g., OpenAI GPT, Google Gemini) to create intelligent interfaces and solutions.

- Manipulate and visualize data using NumPy, Pandas, Matplotlib, and Seaborn.

- Work with NoSQL databases (e.g., MongoDB, Redis) for scalable data storage and retrieval.

- Operate and deploy solutions effectively in Linux-based environments.

- Participate in code reviews, debugging, and performance optimization.

- Follow through on assigned action items, timelines, and deliverables in an Agile delivery model.

Ideal Candidate :

- Must have 4+ years of experience in backend development using Python

- Must have 1+ year of experience in Machine Learning, Deep Learning, NLP, text classification, and image classification projects

- Hands-on experience with Computer Vision technologies such as YOLO, OpenCV, OCR, Tesseract, and EasyOCR

- Strong experience in building and maintaining scalable APIs and inference services using FastAPI

- Expertise in Python, FastAPI, Machine Learning, Deep Learning, NLP, OpenCV, YOLO, OCR, TensorFlow/PyTorch, ETL pipelines, NumPy, Pandas, and NoSQL databases

- Hands-on experience with Generative AI models and tools such as OpenAI GPT, Gemini, Claude, or LLaMA

- Experience working with MongoDB, Redis, Linux environments, and production-grade AI/ML systems

- AI-first startups, product companies, SaaS organizations, fintech, or data-driven technology companies.