AI Developer

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Summary:

The AI Developer Analyst will design and develop intelligent applications leveraging both open-source and commercial AI models with a focus on scalable containerized solutions. This role combines software engineering AI expertise and agile project leadership in a research-focused environment. The incumbent will have a deep experience in Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) and modern cloud AI platforms including but not limited to Azure AI and Google Vertex AI.

Duties and Responsibilities:

• Design develop and deploy intelligent applications using LLMs (e.g. GPT PaLM open-source models like LLaMA Mistral or Falcon etc).
• Implement Retrieval-Augmented Generation pipelines to enhance model performance on domain-specific tasks.
• Integrate and coordinate multiple AI agents and models to solve complex problems.
• Utilize cloud-based AI platforms for model training deployment and serving.
• Leverage APIs from both commercial (OpenAI Anthropic Google Azure) and open-source LLM providers (Hugging Face

Ollama vLLM).

• Deploy AI models and agents using containerization tools (Docker Kubernetes/GKE/AKS).
• Work within Agile AI development workflows including project scoping sprint planning and iterative delivery.
• Train and fine-tune models using Python frameworks (e.g. TensorFlow PyTorch JAX).
• Access and manage models through cloud ML pipelines model registries and experiment tracking tools.
• Maintain high-quality code with Git CI/CD and code review processes.
• Collaborate with interdisciplinary teams to define goals gather requirements and translate them into working systems.
• Create and implement policies initiatives and specifications that support the strategic direction of a faculty/department/unit and meet ethics board requirements.
• Assist in the development of application documentation user documentation and training materials

Requirements

Education: Undergraduate Degree

Experience: Three (3) years related experience

Desired: Bachelors or Masters degree in Computer Science Computer Engineering Software Engineering or a related field.

Skills & Expertise:

• Proven experience with LLMs and RAG systems both commercial and open-source.
• Proficiency in Python and leading ML libraries (TensorFlow PyTorch Transformers).
• Hands-on experience with Google Cloud (Vertex AI PaLM/Gemini BigQuery ML) and Azure AI (Azure OpenAI Azure ML).
• Experience deploying containerized AI systems (Docker Kubernetes).
• Competent in accessing configuring and scaling models from Hugging Face and other open repositories.
• Strong understanding of prompt engineering model fine-tuning and inference optimization.
• Agile development mindset with experience in small project planning task management and stakeholder engagement.
• Familiarity with model orchestration frameworks (e.g. LangChain Haystack Semantic Kernel).
• Understanding of data governance and responsible AI practices in cloud environments.
• Ability to break down complex problems and communicate solutions clearly to technical and non-technical audiences.
• Experience integrating AI into broader platforms or research ecosystems.
• Knowledge of French and English. McGill University is an English-language university where day to day duties may require English communication both verbally and in writing.

Before applying please note that to work at McGill University you must be both authorized to work in Canada and willing to work in the province of Quebec at the campus where the position is based / located.

Knowledge of English: McGill University is an English-language university where day to day duties may require English communication both verbally and in writing. The level of English required for this position has been assessed at a level # (qualifier) on a scale of 0-4.

For a definition of our language proficiency levels please click here.

Job Profile: