AI/ML Engineer Intern (2027)

Posted 25 Days Ago
Headquarters, AZ, USA
Hybrid
Internship
Angel or VC Firm • Software
The Role
Support development of LLM agents, RAG pipelines, and fine‑tuned models. Contribute to portfolio projects, run experiments and ablations, prepare technical documentation and demos, assist discovery workshops, and help implement evaluation and governance pipelines.
Summary Generated by Built In
About Georgian

Georgian is a Toronto-based venture capital firm that partners with high-growth technology companies across cybersecurity, AI software, robotics, defense. We manage about $6B in assets and we have invested in more than 80 companies that we support with capital and technical capability.

Our in-house AI lab works directly with portfolio companies to provide a differentiated experience across the investment lifecycle, and drives the adoption of AI for our internal operations.

 
About the Role

Are you an aspiring AI Engineer eager to gain real-world impact and learn how to push AI's boundaries? Imagine diving into diverse, cutting-edge AI problems across multiple high-growth companies with the support of a leading VC firm. That's Georgian.

We're not your typical VC. Georgian's unique R&D team partners directly with our portfolio companies, providing the technical horsepower and strategic guidance to help accelerate their AI initiatives. We also play a critical role in our investment process, conducting deep technical diligence to identify promising AI-driven businesses.

Think of it as working in a dynamic startup environment, but without the inherent risks of a single venture. You'll tackle fascinating challenges, meet and potentially work with brilliant founders and CTOs, and try to help unearth the next generation of industry leaders. It's a fun, engaging, and highly impactful way to build your career.

Why This Role Exists

Georgian's mission is to empower the world's leading B2B software companies with an unfair advantage, accelerating their participation in the digital economy. As an AI Engineer Intern on our R&D team, you'll support this mission by contributing to cutting-edge machine learning projects. You'll assist in bringing machine learning expertise directly to our portfolio companies' most pressing challenges, helping them build and scale potentially transformative AI products. You'll also contribute to our investment process technical diligence, helping us identify innovative and technically sound companies.

What You'll Own & Deliver

  • Support AI system development. Assist in building LLM agents, Retrieval‑Augmented Generation (RAG) pipelines and fine‑tuned domain‑specific models under guidance; help implement workflows with frameworks like LangChain/LlamaIndex/PydanticAI.

  • Contribute to portfolio projects. Support Georgian "strike teams" embedded in portfolio companies; assist with code implementation, testing, and documentation.

  • Technical analysis & documentation. Help convert technical concepts into clear documentation; support preparation of demos and presentations for stakeholders.

  • Hands‑on R&D support. Assist in rapid prototyping, run experiments and ablation studies, contribute to internal tech notes and documentation.

  • Support AI roadmap development. Help gather requirements in discovery workshops, assist in documenting technical specifications and implementation plans.

  • Contribute to safety & governance. Assist in implementing evaluation pipelines and testing frameworks to keep models reliable and compliant.

What We're Looking For

Ideal Attributes
  • Education & Experience: Currently pursuing or recently completed a Master's or PhD degree in Computer Science, Electrical Engineering, Statistics, or a related quantitative discipline with a focus on machine learning, optimization theory, or related areas.

  • Hands-On Foundation: Familiarity with deep learning toolkits such as Scikit-learn, TensorFlow, or PyTorch. Understanding of GenAI, LLM tooling and Context Engineering fundamentals.

  • Software Development: Proficiency in Python and foundational software development skills, enabling you to write clean, efficient code.

  • Problem Formulation & Communication: The ability to understand applied research problems, assist in designing experiments, implement solutions, and clearly document findings for diverse audiences with varying technical backgrounds.

  • Collaboration: Demonstrated ability to work on team projects, collaborate effectively with technical groups, and communicate progress to mentors and stakeholders.

Nice-to-Haves
  • Experience contributing to open-source AI/ML-related projects or research papers.

  • Familiarity with cloud platforms (AWS, GCP, Azure) for MLOps and model deployment.

  • Exposure to specific industry verticals relevant to Georgian's portfolio (e.g., vertical SaaS, cybersecurity, healthcare tech, fintech).

Cultural attributes we love

  • High ambition & agency: You're allergic to incrementalism and thrive in low‑structure, high‑ownership settings.

  • Insatiable curiosity: You debug the root cause and ask why until everyone else gets annoyed—in a good way.

  • Team over ego: You amplify colleagues and founders alike, seeing leverage in elevating the collective.

  • Commercial storytelling: You speak with brevity and distill complexity so a time‑starved CEO instantly sees value.

Hiring Process

We don't hire like a MAG7 or scale up — in fact we rarely hire compared to them.

You shouldn't expect a cookie-cutter high-volume hiring process with us — but a more boutique one that allows you to see a lot of the organization before joining us.

We build a thesis in what an individual brings to our very small team, versus simply matching qualifications:

  1. 30‑min intro (values & motivations)

  2. 60‑min technical interview (ML fundamentals & problem‑solving)

  3. Project discussion with team members

Position Status
 

This posting represents an active, future internship vacancy on our team. We will be interviewing for this role in the fall.

 
Our Commitment to Accessibility

Georgian is dedicated to building an inclusive environment where everyone can thrive. We provide reasonable accommodations throughout our recruitment process to ensure every candidate has the opportunity to perform at their best. If you require any specific accommodations at any stage, please reach out to us at peopleteam [at] georgian.io.

Use of AI

Innovation is at our core and we use artificial intelligence (AI) to support parts of our hiring process, such as screening and evaluating applications. These tools are designed to assist - not replace - human decision making and all final hiring decisions are made by our team. We regularly review our AI tools to help promote fairness and reduce the risk of unintended bias. If you have any questions about how we use AI in our process or would like more information, please contact us at careers [at] georgian.io.

Skills Required

  • Currently pursuing or recently completed Master's or PhD in Computer Science, Electrical Engineering, Statistics, or related quantitative discipline
  • Familiarity with deep learning toolkits such as Scikit-learn, TensorFlow, or PyTorch
  • Understanding of Generative AI, LLM tooling, and Context Engineering fundamentals
  • Proficiency in Python and foundational software development skills
  • Ability to design experiments, implement solutions, run prototypes/ablation studies, and document findings
  • Demonstrated ability to collaborate on team projects and communicate progress to stakeholders
  • Familiarity with workflows and frameworks like LangChain, LlamaIndex, or PydanticAI
  • Experience contributing to open-source AI/ML projects or publishing research papers
  • Familiarity with cloud platforms (AWS, GCP, Azure) for MLOps and model deployment
  • Exposure to industry verticals relevant to Georgian's portfolio (e.g., vertical SaaS, cybersecurity, healthcare tech, fintech)
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The Company
137 Employees
Year Founded: 2008

What We Do

Georgian is a Toronto-based growth equity investment firm focused on market-leading, high-growth B2B software companies. It invests in businesses across the AI technology stack, particularly in Applied AI and Trust, while also building software to help portfolio companies scale faster. Its team combines investors, machine-learning professionals, software entrepreneurs, and experienced operators, offering both investment expertise and software-enabled growth support.

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