Description:

As a Machine Learning Engineer at Interview Kickstart, you will develop and deploy cutting-edge AI/ML solutions that enhance the platform and improve the learning experience for students.
You will collaborate closely with data scientists, engineers, and product managers to build and scale robust and impactful machine learning models.
Your responsibilities will include working with experienced developers to create and deploy machine learning solutions that drive growth and enhance learner experiences through AI.
You will interact with stakeholders to clearly define business challenges and translate these challenges into actionable machine learning projects.
Researching, experimenting, and iterating to discover and implement optimal methods for solving identified problems will be part of your role.
Staying informed about recent developments in AI/ML, including key publications, best practices, evaluation methodologies, technology stacks, and relevant tools is essential.
If you have expertise or interest in Generative AI, Retrieval-Augmented Generation (RAG), NLP, or transformer-based models, you will have opportunities to contribute to projects requiring them.

Requirements:

You must have 3.5+ years of full-time experience at tier-1 product-based companies building statistical and machine learning models to address real-world business problems.
Proficiency in Python is required.
A deep understanding of foundational concepts in statistics, probability, linear algebra, and calculus is necessary.
Proven expertise in traditional machine learning methods (e.g., regression, classification, clustering, tree-based models) and deep learning techniques (e.g., neural networks, CNNs, RNNs) is essential.
Excellent communication skills are required, with the ability to present insights clearly to both technical and non-technical audiences.
Strong quantitative abilities supported by an advanced degree in fields like computer science, engineering, machine learning, statistics, or mathematics are necessary.
Experience in productionizing and maintaining machine learning models on cloud platforms (e.g., AWS, Azure, GCP) is a plus but not mandatory.

You will have complete ownership of your projects, allowing you to experiment, fail, and learn.
You will work with a high pedigree, high caliber team that values contribution to every area of the business.
Your work will have a real impact, providing you with the opportunity to contribute significantly to the organization.
The position offers top-of-the-line compensation, reflecting the value of your contributions.