Applied AI Engineer Intern

The Opportunity

We’re seeking an Applied AI Engineer Intern to join Parspec in Summer 2026 (start date flexible). This role is part of the AI team and works closely with Product and Engineering on fast-moving, real-world applications of AI.

As an intern, you’ll apply modern AI and machine learning techniques to concrete product problems, such as understanding product specifications, improving product recommendations, and exploring early agentic AI workflows, while learning how AI systems are designed, built, evaluated, and shipped in the real world.

This is an ideal role for a student who wants hands-on experience applying AI to complex, messy industry data and customer-facing product workflows.

What You Will Achieve and Key Responsibilities

• Contribute to AI-driven initiatives, from problem framing through experimentation and implementation
• Build, prototype, evaluate, and iterate on models and AI-powered workflows used in customer-facing product features
• Partner with Senior Applied AI Engineers and Product Managers to translate real customer problems into clear technical approaches and tradeoffs
• Analyze structured and unstructured data (e.g., product specifications, documents, metadata) to improve model performance
• Document assumptions, results, and learnings to support cross-functional alignment and decision-making

Why This Matters

Construction remains one of the world’s largest and least digitized industries. Construction teams rely on manual workflows to interpret product specifications, identify suitable materials, compare options, and make procurement decisions. Parspec applies AI to power workflows that help stakeholders evaluate products, surface better options, and act with confidence. As an Applied AI Engineer Intern, your work will directly support these capabilities and the decisions they enable.

Who You Are

You’re excited about applying AI to real-world problems that don’t come neatly packaged. You enjoy breaking down complex systems, working with imperfect data, and experimenting to find practical solutions. You’re curious, technically grounded, and comfortable collaborating with Product and Engineering partners to balance model performance, system constraints, and customer impact.

Qualifications

• Currently enrolled in a US-based, degree-seeking program (Bachelor’s, Master’s, or PhD) in Engineering, Computer Science, or related fields
• Strong familiarity with core ML/AI concepts and tooling, such as model training (LoRA/QLoRA) and evaluation, embeddings, RAG systems, agentic frameworks like LangGraph, CrewAI or related techniques.
• Strong familiarity with ranking and recommendations techniques.
• Hands-on experience applying AI or machine learning to real-world projects, including working with imperfect data, making tradeoffs, and iterating based on results
• Strong analytical and problem-solving skills
• Ability to work effectively in ambiguous problem spaces with guidance and mentorship
• Clear written and verbal communication skills for technical and non-technical audiences.

Preferred Qualifications

• Exposure to B2B SaaS products, especially workflow-heavy or operations-focused software
• Interest in or exposure to construction industry workflows, including materials procurement