Jr. AI/ML Python Engineer

Experience Level - 0 to 2 Years Location - Pune

Role Summary The Entry-Level AI/ML Python Developer will assist the Senior Data Science and Engineering teams in building, training, and deploying robust machine learning models and data-driven solutions. This role is ideal for a recent graduate with strong foundational knowledge in Python programming, core ML algorithms, and a passion for data analysis and innovation.

Key Responsibilities Data Pipeline Assistance:

Help with data collection, cleaning, preprocessing, and feature engineering using libraries like

Pandas

and

NumPy . Model Implementation:

Write, test, and maintain clean and efficient Python code for implementing and experimenting with various machine learning models (e.g., regression, classification, clustering). Code Development:

Contribute to the development of production-ready code, focusing on code quality, modularity, and adherence to company standards. Experimentation:

Run and document model training experiments, analyze results, and generate performance metrics. Tooling:

Utilize version control systems, primarily

Git , to manage code repositories and collaborate effectively. Learning & Research:

Proactively learn new algorithms, tools, and best practices in the AI/ML space to support team objectives.

Required Qualifications & Skills Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a closely related quantitative field.

Technical Skills (Must-Have) Programming:

Strong proficiency in Python and familiarity with Object-Oriented Programming (OOP) concepts. ML Fundamentals:

Solid understanding of core Machine Learning concepts and algorithms (e.g., Linear/Logistic Regression, Decision Trees, K-Means). Libraries:

Hands-on experience with fundamental Python libraries: NumPy, Pandas, Matplotlib, scikit-learn. Version Control:

Experience using Git and GitHub/GitLab/Bitbucket. Mathematics: Foundational knowledge of Statistics, Linear Algebra, and Calculus relevant to machine learning.

Preferred Skills (Nice-to-Have) Familiarity with deep learning frameworks like TensorFlow or PyTorch. Basic understanding of cloud platforms (AWS, Azure, or GCP) and related services. Experience with query languages like SQL. Completed personal projects or successful participation in hackathons/Kaggle competitions demonstrating practical ML application.

.