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About the role

  • Research Intern at Mila focusing on advanced AI projects and culturally relevant content creation methodologies in collaboration with engineering teams.

Responsibilities

  • **Main responsibilities**
  • Design, formalize and explore different strategies (explicit, implicit and structured) to influence model behavior (prompt rewriting, contextual instructions, RAG).
  • Implement rigorous comparative evaluation protocols and define precise metrics to measure cultural relevance, response diversity and the overall usefulness of outputs.
  • Iteratively test and compare the performance of developed strategies across multiple state-of-the-art models (e.g., GPT, Claude, Gemini).
  • Build a "golden dataset" of culturally ambiguous or representative test queries covering domains such as film, music, media and literature.
  • Develop simple interfaces, dashboards or interactive notebooks to compare models in parallel and facilitate easy annotation of results.
  • Leverage and analyze real interactions from the MCP (Model Context Protocol) system to understand agents' responses to steering signals and turn these logs into research insights.
  • Identify effective approaches, study trade-offs between local relevance and global usefulness, and produce a final research report with the potential to contribute to academic publications.
  • Contribute to cutting-edge research on foundational models, language models or vision models and their industrial applications.
  • Implement solutions and experiment with pre-trained foundational models.
  • Adapt the latest VLM and LLM architectures, training techniques and evaluation pipelines for domain-specific applications.
  • Propose and investigate innovative research directions to improve the team’s internal prototypes.
  • Analyze system performance and contribute to iterative improvements through experimentation and testing.

Requirements

  • **Candidate profile**
  • Enrolled in a PhD program or near completion of a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP) or a related technical field.
  • Strong skills in experimental methodology, test protocol design and qualitative/quantitative model evaluation.
  • Practical, hands-on experience with LLMs, RAG systems or agentic architectures.
  • Proficiency in the Python programming language and ability to design a simple experimentation interface or tool (dashboards, interactive notebooks).
  • Excellent ability to collaborate and bridge research and engineering teams.
  • Currently a graduate student or recent graduate at the master’s or doctoral level in Computer Science, Applied Mathematics, Machine Learning, Computer Vision or a related technical field.
  • Good understanding of machine learning, especially deep learning.
  • Knowledge of foundational models and deep learning model architectures.
  • Experience with programming languages, notably Python, and frameworks such as PyTorch.
  • Research skills with the ability to stay up to date with the latest trends in AI and machine learning.
  • Solid understanding of machine learning and computer vision.
  • Excellent applied research skills, including problem definition, solution exploration, and analysis and presentation of results.
  • Strong problem-solving skills and a passion for innovation.
  • Intermediate proficiency in French and English, due to interactions you will have in the role with some of our partners, stakeholders or members of our anglophone academic community.
  • **Additional assets**
  • Demonstrated interest in issues of local cultural representation, diversity and the societal impact of AI (particularly in the Québécois and Francophone context).
  • Familiarity with the MCP (Model Context Protocol) server ecosystem or other steering-layer infrastructures.
  • Prior experience integrating commercial large model APIs (OpenAI, Anthropic, Google, etc.).
  • Previous experience in Natural Language Processing (NLP) or vision models.
  • Experience training/fine-tuning and evaluating vision-and-language models.
  • Knowledge of recent multimodal alignment techniques and experience with large multimodal datasets (image-text-audio).
  • Familiarity with limitations and challenges in vision-language modeling.
  • Experience in rapid prototyping using AI platforms for model development and refinement.
  • Exposure to generative AI tools and pipelines, including APIs for annotation and data curation (e.g., GPT-4), is a plus.

Benefits

  • **We want to hear from you**
  • At Mila, diversity matters to us. We value a fair, open and respectful work environment that embraces differences. We encourage anyone who wishes to contribute to an evolving, stimulating ecosystem and to help build and sustain a healthy, inclusive culture to apply.
  • Please note that only selected candidates will be contacted.
  • https://mila.quebec/fr/protection-de-la-vie-privee

Job title

Job type

Internship

Experience level

Entry level

Salary

Not specified

Degree requirement

Postgraduate Degree

Tech skills

PythonPyTorch

Location requirements

HybridMontrealCanada

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