AI/ML Engineer

Introduction

Kickstart your career with NTTS’s G.L.O.W Graduate Program, the ultimate launchpad for your tech career!

G – Grow in accelerated development path

L – Lead yourself with purpose & commitment

O – Own your career journey

W – Way Forward

Our comprehensive one-year program is tailored to empower talented and driven graduates like you with valuable hands-on experience, exposure to industry experts, and a diverse range of projects that will sharpen your skills and broaden your understanding to the ICT industry.

AI / ML Engineer

We are looking for an enthusiastic Associate AI/ML Engineer to join our innovation-driven team. This role is ideal for early-career professionals eager to apply machine learning and AI techniques to enhance software applications, automate workflows, and deliver intelligent solutions for our clients across various industries.

Responsibilities

• Collaborate with software engineers and integration specialists to embed AI/ML capabilities into web and enterprise applications.
• Assist in designing, training, and deploying machine learning models for use cases such as predictive analytics, recommendation systems, and intelligent automation.
• Work with structured and unstructured data from APIs, databases, and third-party systems to build robust data pipelines.
• Support the integration of AI services with existing applications using RESTful APIs and microservices architecture.
• Participate in code reviews, testing, and documentation to ensure high-quality deliverables.
• Monitor model performance in production and assist in continuous improvement efforts.
• Stay current with emerging AI/ML tools and frameworks relevant to application development and integration.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field.
• Proficiency in Python and familiarity with ML libraries such as scikit-learn, TensorFlow, or PyTorch.
• Understanding of software development principles and experience with version control systems (e.g., Git).
• Familiarity with REST APIs, JSON, and integrating ML models into web-based applications.
• Experience with SQL and NoSQL databases; knowledge of ETL processes is a plus.
• Exposure to cloud platforms (AWS, Azure, or GCP) and containerization tools (e.g., Docker) is advantageous.
• Strong problem-solving and analytical thinking.
• Effective communication and collaboration in cross-functional teams.
• Willingness to learn and adapt in a fast-paced, client-focused environment.