AI/ML Engineer

As an AI/ML Engineer, your primary responsibility is to design, train, and deploy machine learning models that directly impact products used by millions of users.

You will begin by understanding the problem — for example, recommendation systems, fraud detection, search ranking, or predictive analytics. You will then work with large datasets to clean, preprocess, and prepare features.

You will build machine learning models using algorithms such as regression, classification, clustering, or deep learning. Model selection, tuning, and evaluation will be key parts of your workflow.

You will also focus on scalability. Your models should not just work on small datasets but must perform efficiently on large-scale distributed systems.

Once models are trained, you will deploy them using APIs or batch pipelines. Monitoring model performance, handling data drift, and updating models will be part of your responsibilities.

Job Requirements

Strong Python programming skills are required. You should be comfortable using libraries such as NumPy, Pandas, and Scikit-learn.

Experience with deep learning frameworks such as TensorFlow or PyTorch is important. You should understand model training, loss functions, and optimization techniques.

You must have experience working with data — cleaning, transforming, and analyzing large datasets. SQL knowledge is essential.

Understanding of system design and scalability is required. Experience with tools like Spark or Hadoop is a plus.

You should also be familiar with deploying models using APIs or cloud services.