AI/ML Intern: Time-Series & LLMs for IoT

Reply; Chicago (IL); On-site; USD 41,000 - 55,000; Part time

Job summary

Concept Reply, part of the Reply Network, is seeking a Computer Science or Computer Engineering graduate for an internship contributing to AI-driven and data engineering solutions. You will work alongside our data and AI engineering team on real client-facing deliverables.

Responsibilities include building ML/AI models, experimenting with LLMs, developing backend services and data pipelines, and creating dashboards for stakeholders. Ideal candidates have strong Python skills and ML coursework.

Qualifications

• Bachelor’s degree completed in CS/CE or related field — not currently enrolled in university.
• Strong foundation in data structures, algorithms and programming fundamentals.
• Proficiency in Python.
• Coursework or project experience in ML / data science.

Responsibilities

• Support development and evaluation of ML/AI models, including forecasting and time-series.
• Assist in experimentation with LLMs, including fine-tuning and deployment of models for applied use cases.
• Contribute to backend services, APIs and data pipelines supporting AI/data solutions.
• Help build internal tools and dashboards for data visualization and stakeholder reporting.
• Collaborate with senior engineers on assigned tech workstreams with growing autonomy.

Skills

Python

Data structures

Algorithms

Machine learning

LLMs

Time-series models

Data visualization

Education

Bachelor’s degree in Computer Science or Computer Engineering

Tools

PyTorch

TensorFlow

scikit-learn

Job description

Concept Reply, part of the Reply Network, is seeking a Computer Science or Computer Engineering graduate for an internship contributing to AI-driven and data engineering solutions. You will work alongside our data and AI engineering team on real client-facing deliverables.

Responsibilities include building ML/AI models, experimenting with LLMs, developing backend services and data pipelines, and creating dashboards for stakeholders. Ideal candidates have strong Python skills and ML coursework.