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.
