<p>About the Role : </p><p><br/></p><p>We are seeking highly motivated and analytical early-career engineers who are passionate about data, artificial intelligence, and problem-solving.
</p><p><br/></p><p>As a Junior AI & Data Engineer, you will gain hands-on experience working with real-world datasets, supporting AI/ML model development, and building scalable data pipelines.
</p><p><br/></p><p>This role provides an opportunity to learn directly from experienced Data Scientists and AI Engineers, laying a strong foundation in Data Science, Machine Learning, and Data Engineering practices.
</p><p><br/></p><p>Key Responsibilities : </p><p><br/></p><p>- Assist in data acquisition, cleansing, transformation, and feature engineering to prepare datasets for machine learning and analytics projects.
</p><p><br/></p><p>- Develop and maintain Python-based ETL scripts for data extraction and processing using libraries such as pandas, NumPy, and scikit-learn.
</p><p><br/></p><p>- Support the development, training, and validation of supervised and unsupervised ML models (e.g., regression, classification, clustering).
</p><p><br/></p><p>- Build data visualizations and dashboards to communicate trends and insights using tools like Power BI, Tableau, or matplotlib.
</p><p><br/></p><p>- Work collaboratively with senior engineers to design and implement scalable data pipelines on cloud environments (AWS, GCP, or Azure).
</p><p><br/></p><p>- Participate in code reviews, documentation, and version control (Git) to maintain development standards and reproducibility.
</p><p><br/></p><p>- Continuously learn and apply emerging practices in AI model deployment, MLOps, and Data Engineering.
</p><p><br/></p><p>Required Skills & Qualifications : </p><p><br/></p><p>- Programming : Strong proficiency in Python with experience using data libraries such as pandas, NumPy, and scikit-learn.
</p><p><br/></p><p>- Data & Statistics : Solid understanding of descriptive statistics, probability, correlation, and linear algebra fundamentals.
</p><p><br/></p><p>- Databases : Basic knowledge of SQL and relational database concepts.
</p><p><br/></p><p>- Analytical Thinking : Strong logical reasoning, problem-solving, and mathematical aptitude.
</p><p><br/></p><p>- Version Control : Basic familiarity with Git/GitHub workflows.
</p><p><br/></p><p>- Eagerness to learn and adapt to AI, Machine Learning, and MLOps technologies in a fast-paced environment.
</p><p><br/></p><p>Preferred Skills (Good to Have) : </p><p><br/></p><p>- Exposure to cloud platforms (AWS, GCP, or Azure).
</p><p><br/></p><p>- Hands-on experience with data visualization or exploratory analysis (Tableau, Power BI, matplotlib, seaborn).
</p><p><br/></p><p>- Familiarity with REST APIs, Jupyter Notebooks, and scripting for automation.
</p><p><br/></p><p>- Participation in Kaggle competitions, academic AI projects, or open-source data projects.
</p><p><br/></p><p>- Passion for mathematics, data-driven problem solving, and continuous learning.</p> (ref:hirist.tech)