Live opening · Posted 1 day ago

Generative AI Engineer

Neeraj Bhagat & Co. · New Delhi, Delhi, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanyNeeraj Bhagat & Co.
LocationNew Delhi, Delhi, India (On-site)
Work modeNo
SourceLinkedin
Listed1 day ago

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About the role

Description supplied by the original job listing.

Role Overview
We are seeking a highly motivated and talented AI/ML Engineer to join our team. The ideal candidate will have a strong background in Python, Pandas, Machine Learning and AI and be eager to work on cutting-edge technologies in the field of data science.
Key Responsibilities
Develop and implement machine learning models to solve complex business problems.
Work with cross-functional teams to gather requirements and translate them into actionable insights.
Analyse and interpret large datasets to identify trends and patterns.
Build and maintain machine learning pipelines and workflows.
Collaborate with data engineers to ensure data quality and accuracy.
Stay up to date with emerging trends and technologies in the field of data science.
Required Qualifications
7-8 years of overall experience, including hands-on experience in Python, Pandas, Machine Learning, and AI.
Bachelor's degree in Computer Science, Mathematics, Statistics or a related field.
Strong knowledge of machine learning algorithms, data analysis and data visualisation.
Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
Ability to work with large datasets and databases.
Good understanding of statistics and experience using statistical techniques to solve problems.
Strong communication and collaboration skills.
Passion for continuous learning and staying up to date with emerging trends and technologies in the field of data science.
Preferred Skills
Working knowledge of the MERN stack (MongoDB, Express.js, React, Node.js), to support full-stack integration and deployment of AI/ML models into production applications.
Key Competencies
Machine Learning & AI Model Development
Data Analysis & Visualization
Deep Learning Frameworks (TensorFlow, PyTorch, Keras)
Statistical Analysis
Full-Stack Awareness (MERN)
Cross-functional Collaboration
Continuous Learning

Work arrangement
No

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