Artificial Intelligence Intern

Company Description

At WorkElate, AI is not a feature it is the engine that plans, nudges, and gets work done. The WorkElate AI Orchestration (WAO) platform turns scattered tasks, chats, and updates into living workflows that plan better, follow up automatically, and close the loop without constant human chasing. WAO uses agentic AI, automations, and conversational and voice interfaces to create flows where tasks are created, delegated, reminded, and tracked with minimal friction for teams. If you want to see AI move beyond prompts and actually run real-world work, this is where you build it.

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Role Description

This is a full-time, remote Artificial Intelligence Intern role focused on building intelligent workflows, not just standalone models. You will work closely with the AI and product engineering teams to prototype and improve LLM-powered features that plan tasks, follow up across channels, and execute actions using automation and nudges (conversational and voice). From transformers and vector databases to RAG and context engineering, you will get hands-on exposure to how modern AI systems are wired into real products that teams use every day.

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What You Will Work On:

1. Experiment with transformer-based models and LLM APIs to power conversational, workflow-aware assistants inside WorkElate.
2. Help design and test Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., pgvector, Pinecone, or similar) for semantic search, memory, and grounding.
3. Contribute to context engineering: prompts, memory strategies, session/context windows, and tool calling so agents can reason over tasks, forms, and workflow states.
4. Support building small automations and agent flows that plan next steps, send follow-ups, and trigger actions across workflows—so work actually gets completed, not just logged.
5. Collaborate with engineers to integrate AI components into APIs and simple UIs (web/MERN stack) for conversational and voice-driven experiences.
6. Analyze logs and basic metrics to understand how users interact with AI features and suggest improvements to make flows smoother and more intuitive.

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Qualifications

Strong foundation in computer science fundamentals and solid programming skills in Python; experience with JavaScript (MERN stack) or similar languages is a plus.

​Good understanding of modern deep learning, especially transformers and LLMs, through coursework, projects, or self-learning.

​Familiarity with vector databases and RAG concepts (embeddings, semantic search, retrieval, grounding) or strong willingness and ability to learn them fast.

​Exposure to AI/ML frameworks and tools such as PyTorch, TensorFlow, or popular LLM/RAG libraries.

​Interest in context engineering, memory, and tools/MCP-style integrations that let AI reason over external systems and data.

​Currently pursuing or recently completed a degree in Computer Science, Data Science, Engineering, or a related field.

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Desired Qualities

Execution-first mindset: You care about shipping working flows that solve real user problems more than just building “cool demos”.

​Bias for automation: Whenever you see a repetitive task, your instinct is to script it, automate it, or turn it into an AI-powered workflow.

​Fast learner, fast mover: Comfortable picking up new tools, APIs, and libraries quickly and iterating in short cycles.

​User empathy: Curious about how teams actually work how planning, follow-ups, and execution happen today and motivated to make those flows simpler and more conversational.

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Paid internship of 4-5 months with a stipend of 10K monthly stipend & opportunity for being full timer. We may work 8+ hours at time to be aligned with the world needs... and 6 days a week.