Job
Description
Job Purpose
We are looking for a proactive and versatile AI Engineer to join our Data AI POD team. You will play a key role in building scalable AI systems that span data engineering, ML/DL, Generative AI, and production-grade APIs. This is a hands-on, impact-driven role where problem-solving, analytical thinking, and a deep understanding of both code and data are essential.The ideal candidate will have experience in Text and Image classification, NLP techniques, computer vision (YOLO, OCR), and be comfortable developing backend services in Python/Linux. You will also work with cutting-edge GenAI models like OpenAI GPT and Google Gemini to solve business problems with intelligent automation.Duties and Responsibilities
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.
Required Qualifications and Experience
Required Skills Qualifications Strong experience in Python programming and development in Linux environments.
Solid background in data engineering and ETL pipeline design.
Hands-on experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, Scikitlearn).
Proven experience in NLP tasks and classification problems (text/image).
Experience with YOLO, OCR, and OpenCV for computer vision projects.
Knowledge of Generative AI models like GPT, Gemini, Claude, or LLaMA.
Strong problem-solving and analytical skills; ability to work independently on
complex technical issues. Skilled in building and maintaining FastAPI-based APIs and services.
Proficiency with data manipulation and visualization tools (NumPy, Pandas,
Matplotlib, Seaborn). Experience integrating with NoSQL databases.
Excellent multitasking and project follow-through capabilities in a fast-paced team
environment. Familiarity with Git, VS Code, and modern development practices.
Good to Have Production experience deploying AI/ML models in cloud or on-prem environments.
Experience with MLOps practices, model versioning, and monitoring.
Familiarity with containerized deployment using Docker and/or Kubernetes.
Experience working in a POD delivery model or Agile squads.