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EngineeringNew🎯 Internship

AI Implementation Intern at Sprinto

Sprinto
•2 hours ago
Location

Bengaluru, Karnataka, India

Salary

Competitive

Apply By

ASAP

Views

3

Eligible Batches

🎓 2024 Batch🎓 2025 Batch🎓 2026 Batch

Job Description

Join Sprinto as an AI Implementation Intern in Bengaluru and gain hands‑on experience building AI solutions with cutting‑edge tools.

Roles & Responsibilities

Assist senior engineers in designing and deploying AI models for real‑world business problems Collect, clean, and preprocess datasets to ensure high‑quality training inputs Develop and test prototype algorithms using Python and ML libraries Document model performance, experiment results, and implementation steps Collaborate with cross‑functional teams to integrate AI features into existing products

Requirements

Pursuing B.Tech/B.E. in Computer Science, AI, Data Science or related field Strong programming skills in Python Familiarity with machine learning frameworks such as TensorFlow or PyTorch Basic understanding of data preprocessing, feature engineering, and model evaluation Good analytical mindset and problem‑solving abilities Effective communication and teamwork skills

Eligibility Criteria

B.Tech/B.E. 2024/2025/2026 Batch

Tech Stack & Ecosystem

Machine LearningAILLMData PipelinesPython

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Quick Info

TypeInternship
RoleEngineering
Work Mode🏢 On-site
Eligible Batches
202420252026

Tech Stack

Machine LearningAILLMData PipelinesPython

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Company Insights

Sprinto is rapidly emerging as a leader in compliance automation, and its AI initiatives are at the forefront of transforming how businesses manage risk. As an AI Implementation Intern, you’ll be immersed in a culture that values experimentation, rapid iteration, and data‑driven decision making, giving you exposure to production‑grade pipelines and real client challenges—experience that is hard to find in academic settings. Working at Sprinto also means access to a mentorship network of seasoned AI engineers and product leaders who actively invest in your growth. The company’s flat hierarchy encourages interns to voice ideas, contribute to open‑source tools, and see the tangible impact of their work on enterprise customers, making this role a launchpad for a thriving career in AI engineering.

Interview Guide

Prepare by building at least one end‑to‑end ML project from data collection to model deployment on a cloud platform (e.g., AWS SageMaker or GCP AI Platform). Be ready to discuss the choices you made for data cleaning, feature selection, model architecture, and how you measured performance—this demonstrates practical competence beyond textbook knowledge. During the interview, expect scenario‑based questions that probe your ability to translate business requirements into AI solutions. Practice articulating the trade‑offs between model complexity, latency, and scalability, and rehearse explaining how you would monitor model drift and iterate post‑deployment. Show curiosity by asking about Sprinto’s current AI stack and upcoming challenges, signaling that you’re ready to contribute from day one.