Apprentice-IT

Description du poste:

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 strong 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