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Toronto Headquarters · Toronto, Ontario, Canada
Actively hiring, first seen by us 4 days agoLocation type: HybridFrom the employer’s posting
Employment type: InternshipFrom the employer’s posting
Department: AI LabFrom the employer’s posting
Job title: AI/ML Engineer Intern (2027)
Are you an aspiring AI Engineer eager to gain real-world impact and learn how to push AI's boundaries?
Think of it as working in a dynamic startup environment, but without the inherent risks of a single venture.
Help build LLM agents, RAG pipelines and fine-tuned domain models
Assist with code, testing and documentation for portfolio company projects
Run rapid prototypes, experiments and ablation studies
Implement evaluation pipelines and testing frameworks for model reliability
Support technical diligence on potential investments
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.
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.
Assist in building LLM agents, Retrieval‑Augmented Generation (RAG) pipelines and fine‑tuned domain‑specific models under guidance
assist with code implementation, testing, and documentation
Assist in rapid prototyping, run experiments and ablation studies
Assist in implementing evaluation pipelines and testing frameworks to keep models reliable and compliant
You'll also contribute to our investment process technical diligence
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.
Georgian is a Toronto-based venture capital firm that partners with high-growth technology companies across cybersecurity, AI software, robotics, defense.
In the employer’s words · Read in context · Company website ↗
Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 4
Early. Similar jobs usually come down between day 8 and day 76.
From 5,517 similar postings that came down. Coming down is not always a hire.
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Open jobs by the week we first saw them, last 12 weeks.
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- 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.
- 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).
- 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.
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
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 ExistsGeorgian'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 & DeliverSupport 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.
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.
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).
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.
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:
30‑min intro (values & motivations)
60‑min technical interview (ML fundamentals & problem‑solving)
Project discussion with team members
This posting represents an active, future internship vacancy on our team. We will be interviewing for this role in early 2027.
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 AIInnovation 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.
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Toronto, Ontario, Canada
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