Position: Junior AI/ML Engineer

Location: Atlanta, GA

Experience: 0-2 Years

Employment Type: Full-Time

Work Mode: Remote (Work From Home)

We provide structured training, real-time project exposure, interview preparation, and continuous support to help you grow successfully in your

career.

Role Overview

We are looking for recent graduates or early-career professionals with 0-2 years of experience to join our Artificial Intelligence and Machine

Learning team. The ideal candidate will assist in developing, training, and deploying AI/ML models while working with large datasets and

cloud-based machine learning solutions. This role is an excellent opportunity for candidates who want to build practical experience in Artificial

Intelligence, Machine Learning, Deep Learning, and MLOps.

Key Responsibilities

Develop, train, test, and deploy Machine Learning models.
Collect, clean, and preprocess structured and unstructured datasets.
Build predictive models using supervised and unsupervised learning techniques.
Work with Python and ML libraries to develop AI solutions.
Perform feature engineering and model optimization.
Collaborate with Data Scientists, Data Engineers, and Software Developers.
Develop data pipelines for AI/ML workflows.
Deploy ML models using cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
Monitor model performance and retrain models when necessary.
Create technical documentation and present project findings.
Follow AI ethics, data governance, and security best practices.
Stay updated with the latest AI, ML, and Generative AI technologies.

Required Skills & Qualifications

0-2 years of experience or knowledge in Artificial Intelligence or Machine Learning.
Strong programming skills in Python.
Basic knowledge of SQL and relational databases.
Understanding of Machine Learning algorithms and model evaluation techniques.
Familiarity with Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
Basic understanding of Deep Learning and Neural Networks.
Knowledge of AWS, Azure, or GCP cloud platforms.
Familiarity with Git, Linux, and Jupyter Notebook.
Exposure to MLOps concepts and Docker is a plus.
Strong analytical, communication, and problem-solving skills.
Ability to work independently and collaboratively in a remote work environment.

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