What you’ll do:

We are looking for a motivated AI/ML Engineering graduate to join our Artificial Intelligence and Machine Learning (AIML) team. This role is ideal for a fresher with a robust academic foundation in AI/ML who is eager to apply theory to real world business problems under mentorship.
You will work closely with senior AI/ML engineers, data scientists, and platform teams to build, experiment with, and operationalize machine learning solutions on enterprise scale data platforms.

- Assist in building and training machine learning models for structured and unstructured data use cases
- Perform data analysis, preprocessing, and feature engineering on large datasets
- Support experimentation using AutoML and custom ML approaches
- Evaluate model performance and assist in tuning for accuracy and robustness
- Work with AI/ML platforms and tools for model development and experimentation
- Collaborate with engineers and analysts to understand business problems and translate them into ML tasks
- Document experiments, learnings, and model outcomes clearly
- Follow best practices for responsible AI, data governance, and security

Qualifications:

- Bachelor’s degree in Engineering (B.E./B.Tech) with specialization in:

o Artificial Intelligence




o Machine Learning
o Data Science
o Computer Science (with strong AI/ML coursework)

Skills:

- Strong fundamentals in:

o Machine Learning algorithms
o Statistics and linear algebra
o Data structures and basic algorithms

- Working knowledge of Python
- Familiarity with ML libraries such as:

o scikit learn
o TensorFlow or PyTorch (basic exposure is sufficient)

- Basic understanding of SQL and working with datasets

Good to Have (Not Mandatory)

- Exposure to:

o Cloud platforms (Azure / AWS / GCP)
o Data platforms like Snowflake
o ML lifecycle concepts (training, evaluation, deployment)

- Academic or personal projects involving:

o Predictive modeling
o NLP or computer vision
o Time series forecasting

- Familiarity with notebooks, Git, or basic MLOps concepts

What You Will Learn

- End to end AI/ML use case development in an enterprise environment
- Working with real production scale datasets
- Model experimentation, evaluation, and promotion practices
- AI/ML platform tools and best practices
- How ML solutions are governed, monitored, and scaled

📌 Apprentice-IT (India)
🏢 Eaton
📍 India