Junior AI/ML Engineer

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.