Machine Learning Engineering at Infrrd

Role Overview

We are looking for a Research Intern to join the team and contribute to experiments that shape what we ship, working on well-scoped research tasks across areas such as agentic document extraction, LLM-based auditing of mortgage documents, table extraction with calibrated trust scores, and verifiable evaluation of model outputs without ground truth.

About Infrrd

Infrrd is an Enterprise AI company that automates document-heavy workflows for customers in mortgage, insurance, and finance. Our Research team works on the next generation of document intelligence: agentic systems that read, reason over, and audit complex documents with outputs that can be trusted and verified.

Key Responsibilities

Design and run experiments to validate document processing and agentic extraction approaches; build prototypes and proof-of-concept implementations using LLM and vision-language model APIs.
Help build evaluation harnesses and verifier checks that measure whether an extraction or audit verdict can be trusted.
Conduct in-depth error analysis on model outputs and agent reasoning traces to identify failure modes, categorise them, and propose fixes.
Verify the quality of datasets and synthetic document packages used in experiments; perform exploratory analysis to understand document characteristics and edge cases.
Assist in converting domain checklist rules into executable, testable checks and in measuring their precision and recall on real documents.

Requirements & Eligibility

10+ 2/PUC mandatory (No Diploma), B.E/B.Tech/M.Tech students from all Computer Science related backgrounds with a focus on machine learning, NLP, or computer vision
Minimum 60% aggregate and higher throughout academics
Strong mathematical, statistical, and probabilistic foundation with a solid grasp of core ML concepts
Strong Python skills, including writing clean, testable code within a larger codebase
Working knowledge of Transformer-based language models and how to use LLM APIs