Intern Argo Data Jobs (NOW HIRING)

Duration: 6-month internship with the possibility to extend based on performance and project needs
Eligibility: U.S. Citizen or Green Card Holder

Overview
We are seeking a motivated Software Engineering Intern to join our technical team and gain hands-on experience across several cutting-edge domains including Business Intelligence (BI), Computer Vision, Artificial Intelligence (AI), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and DevOps.

This internship is ideal for students or early-career technologists who enjoy solving complex problems, experimenting with emerging technologies, and contributing to meaningful, real-world projects. You will work alongside senior engineers on initiatives that support analytics, automation, and AI-driven solutions across our organization.

Key Responsibilities
Computer Vision & AI Projects
· Collaborate on building, training, and testing machine learning or computer vision models.
· Support data preprocessing, image labeling, and model evaluation.
· Assist in developing RAG pipelines, integrating vector databases, and fine-tuning LLMs for internal knowledge systems.
· Use Open WebUI and related frameworks to build and test conversational or AI assistant interfaces.

Automation & Workflow Engineering
· Leverage n8n for building and orchestrating workflow automations between internal systems and APIs.
· Integrate automation into business processes, dashboards, and AI/LLM pipelines.
· Document and version automation workflows for reuse and maintainability.

Data & BI Dashboards
· Assist in designing and developing dashboards using tools such as Power BI, Metabase, or Grafana.
· Work with data engineers to visualize KPIs, operational metrics, and predictive insights.
· Automate data pipelines and ETL processes using SQL, scripting, or n8n automation workflows.

DevOps & Infrastructure
· Learn to deploy and monitor applications using Docker, Kubernetes, and CI/CD pipelines.
· Gain exposure to GitOps tools such as Gitea, Argo CD, and Harbor for container registry and continuous deployment.
· Assist in setting up and maintaining on-premise and cloud environments (AWS, Azure).
· Participate in system automation, observability, and logging/monitoring initiatives.

Collaboration & Documentation
· Work closely with engineers, data scientists, and leadership to deliver prototypes, reports, and production-ready modules.
· Help document APIs, workflows, and system architecture for technical reference.

Desired Skills & Traits
· Strong foundation in one or more programming languages (Python, JavaScript/TypeScript, Java, or C#).
· Solid understanding of SQL and relational databases (MySQL, PostgreSQL, etc.).
· Familiarity with data visualization tools (Power BI, Metabase, Grafana).
· Basic understanding of machine learning frameworks (PyTorch, TensorFlow, or OpenCV a plus).
· Understanding of RAG, vector databases, and LLM integration workflows.
· Experience or interest in automation tools such as n8n.
· Basic knowledge of networking concepts, including DNS, firewalls, and network routing.
· Experience or curiosity about cloud platforms (AWS, Azure) and containerization (Docker, Kubernetes).
· Comfortable using Linux and command-line tools.
· Strong analytical mindset, attention to detail, and eagerness to learn.
· Effective communication and documentation skills.

Learning Outcomes & Goals (First 90–180 Days)
· Build and deploy a computer vision or AI prototype, incorporating LLM and RAG components.
· Develop and deploy APIs for system integrations and AI workflows.
· Design and implement one or more BI dashboards visualizing real operational data.
· Create and automate workflows using n8n to connect data sources, dashboards, and AI services.
· Gain experience with DevOps workflows using Gitea, Argo CD, Harbor, Helm, and Kubernetes.
· Deploy and manage AI interfaces using Open WebUI, integrating internal models and data.
· Present completed projects and findings to the engineering and leadership teams.

Job Type: Internship

Pay: $15.00 - $16.00 per hour

Work Location: In person