AIML Developer

Job Overview

  • Date Posted
    February 14, 2025
  • Company Location
  • Expiration date
    March 16, 2025
  • Experience
    Fresher
  • Gender
    Both
  • Qualification
    B.Sc. (Bachelor of Science), B.Tech (Bachelor of Technology), B.E. (Bachelor of Engineering)
  • Career Level
    Associate

Job Description

1.Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field
2.Basic knowledge or understanding of machine learning algorithms, deep learning, and frameworks like TensorFlow, Keras, or PyTorch
3.Proficiency in Python and basic libraries such as Pandas, NumPy, Matplotlib
4.Understanding of data preprocessing, feature engineering, and model evaluation techniques
5.Passion for solving complex problems using AI/ML techniques
6.Strong analytical, mathematical, and problem-solving skills
7.Ability to work in a collaborative team environment
8.Strong communication skills to interact with cross-functional teams
9.Eagerness to learn and grow in the field of Artificial Intelligence and Machine Learning

Terms and Conditions:

Project Continuation: Based on successful completion of sprints and evaluations during training

Candidate Requirements:

. 100% attendance during training and project phases
. Successful completion of tasks and project goals
. Job offer will be based on performance and management discretion

Roles & Responsibilities:

1.As an AIML Developer (Freshers), you will be a part of a team focused on building AI and ML solutions for real-world problems.
Key responsibilities include:
1.Model Development: Assist in developing machine learning and deep learning models for various use cases
2.Data Processing: Help with preprocessing and cleaning large datasets
3.Algorithm Implementation: Implement AI algorithms for supervised and unsupervised learning
4.Collaboration: Work closely with senior developers and data scientists to enhance AI/ML models
5.Testing and Debugging: Assist in model testing and evaluating performance metrics
6.Documentation: Maintain clear documentation for models and algorithms
7.Learning and Growth: Continuously update skills in the rapidly evolving AI/ML space