AI Engineer / Senior AI Engineer
AI Engineer / Senior AI Engineer
22
Greater Noida
Job Views:
Created Date: 2026-01-13
End Date: 2026-03-13
Experience: 3 - 5 years
Salary: 90000
Industry: Manufacturing
Openings: 1
Primary Responsibilities :
Job Description (JD)
Role: AI Engineer / Senior AI Engineer
Experience: 3–5 Years
Salary: ₹70,000 – ₹90,000 per month
Role Overview
We are looking for a hands-on AI professional with strong experience in Image Analysis (Computer Vision), Data Modeling, and Natural Language Processing (NLP).
This role focuses on building production-grade AI solutions that solve real-world business problems using both structured and unstructured data.
You will work closely with product, engineering, and business teams to translate problem statements into scalable, efficient, and reliable AI models and systems.
Key Skills & Qualifications
3–5 years of hands-on experience in AI/ML development.
Strong experience in both Computer Vision and NLP (mandatory).
Proficiency in Python and ML/DL frameworks (TensorFlow, PyTorch).
Experience working with structured, semi-structured, and unstructured data.
Solid understanding of ML algorithms, model evaluation, and optimization.
Experience deploying models in production environments (APIs, batch jobs, pipelines).
Strong problem-solving skills and ability to work cross-functionally.
Preferred / Nice to Have
Experience with cloud platforms (AWS, GCP, Azure).
Knowledge of MLOps, CI/CD, and model monitoring.
Exposure to large language models (LLMs) and multimodal AI systems.
Experience Requirements:
Key Responsibilities
1. Image Analysis / Computer Vision
Design, develop, and deploy computer vision models for:
Image classification, object detection, and segmentation
OCR, document understanding, visual inspection, and anomaly detection
Build, fine-tune, and optimize deep learning models including CNNs and Vision Transformers (ViTs).
Work with computer vision and deep learning frameworks such as OpenCV, TensorFlow, and PyTorch.
Optimize models for performance, accuracy, latency, and inference efficiency in production environments.
Implement image preprocessing, data augmentation, and annotation/labeling strategies.
Integrate computer vision solutions into end-to-end AI pipelines.
2. Data Modeling & Analytics
Design and maintain robust data models for AI/ML pipelines using structured and semi-structured data.
Perform data exploration, feature engineering, and statistical analysis to support model development.
Build predictive and descriptive models using:
Regression, classification, clustering, and time-series techniques
Ensure data quality, consistency, scalability, and reliability across pipelines.
Collaborate with data engineering teams on ETL processes, data pipelines, and data lake architectures.
3. Natural Language Processing (NLP)
Develop NLP solutions for:
Text classification, entity extraction, sentiment analysis, and document processing
Work with modern NLP techniques including transformers, embeddings, and language models.
Fine-tune and deploy NLP models for production use cases.
Integrate NLP outputs with vision and structured data models where required.