AI/ML

Company Description:

Shrinex Fintech Services is a next-generation B2B fintech SaaS company that enhances how businesses manage their Order-to-Cash and Procure-to-Pay cycles through intelligent automation and compliance. Founded in 2025, we are launching our first solutions in collections intelligence and deduction lifecycle automation. In 2026, we will expand our platform to include behavioral credit risk, intelligent invoicing, and dynamic forecasting solutions. Our services are designed for enterprises in various industries across India, the USA, and EMEA, featuring ERP-agnostic integrations and strong compliance standards. Our mission is to redefine trust in financial transactions through innovative technology.

Responsibilities

Role Description:

As an AI/ML Intern, you will work on real-world problems in invoice automation, collections risk, and NLP-driven finance operations. You will support data science projects from cleaning datasets to developing, evaluating, and deploying AI/ML models directly in Shrinex products.

Job Description

Responsibilities:

● Assist in building, training, and validating machine learning models for document processing, credit risk, and anomaly detection.

● Perform data wrangling, feature engineering, and exploratory data analysis.

● Research and experiment with new algorithms relevant to O2C/P2P automation.

● Collaborate with software engineers to integrate ML solutions into production.

Requirements:

● Strong foundation in Python and key libraries (pandas, NumPy, scikit-learn).

● Understanding of supervised/unsupervised learning, data preprocessing, and model evaluation.

● Ability to read and present ML research papers and documentation.

● Bonus: Familiarity with NLP, deep learning (TensorFlow/PyTorch), or finance datasets.

Qualifications:

● Pursuing or recently completed degree in Computer Science, Data Science, AI, or related.

● Experience in AI/ML hackathons or personal ML projects is a plus.

● Strong analytical and problem-solving mindset.

Duration: 4–6 months

Location: Remote (India preferred)