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Python Llm Jobs in Toronto, ON (NOW HIRING)

ShyftLabs

AI Engineer Intern

Toronto, ON · Hybrid

CA$20 - CA$30/hr

Strong programming skills in Python. * Good understanding of machine learning, natural language processing, and LLM fundamentals. * Experience building at least one LLM-powered or agentic application.

Royal Bank of Canada

Staff Data/AI Engineer

Toronto, ON · On-site

Develop and integrate AI services such as LLM-powered APIs, retrieval-augmented generation (RAG ... Python, Java, SQL, Spark) with strong software engineering fundamentals, including version control ...

Tiger Analytics Inc.

Gen AI Engineer

Toronto, ON · On-site

Strong Python programming skills with a deep understanding of OpenAI API standards, JSON RESTful design, and LLM orchestration. * Preferred Skills: Experience working with Bedrock Agent/Core services ...

Tiger Analytics Inc.

Gen AI Engineer

Toronto, ON · Remote

Strong Python programming skills with a deep understanding of OpenAI API standards, JSON RESTful design, and LLM orchestration. * Preferred Skills: Experience working with Bedrock Agent/Core services ...

Alquemy

Automation Engineer

Toronto, ON · On-site

Python | C++ | C#/.NET | Java | SQL | pytest | GitHub Actions | Jenkins | Docker | Ansible | Git | Oracle/SQL Server | LLM/AI Tools Why Join. Build automation for complex, business-critical ...

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All JobsPython Llm JobsPython Llm Jobs in Toronto, ON

Python Llm information

What is a Python LLM?

A Python LLM job involves working with Large Language Models (LLMs) using Python to develop, fine-tune, and deploy AI models. Responsibilities may include data preprocessing, prompt engineering, model optimization, and integration with applications. Professionals in this role often work with frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. They may also contribute to improving model efficiency, reducing bias, and ensuring ethical AI usage.

What are the key skills and qualifications needed to thrive in the Python LLM position, and why are they important?

To excel as a Python LLM (Large Language Model) Engineer, you need strong skills in Python programming, machine learning, and natural language processing, typically supported by a degree in computer science or a related field. Proficiency with libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and experience with model deployment platforms are often essential, alongside certifications in AI or data science. Effective communication, problem-solving abilities, and collaboration are important soft skills for working in interdisciplinary teams and delivering results in dynamic environments. These skills ensure the development, fine-tuning, and deployment of advanced language models that meet both technical and business objectives.

What are some common challenges faced by Python LLM engineers in their daily work?

Python LLM Engineers often encounter challenges related to optimizing model performance, managing large datasets, and adapting models to specific business needs. Working with large-scale language models requires balancing computational resource limitations with the need for high accuracy and efficiency. Collaboration with data scientists, product managers, and DevOps engineers is routine to ensure seamless model integration and deployment. Staying updated on the latest advancements in NLP and continuously improving models based on user feedback are also important aspects of the role.

What are popular job titles related to Python Llm jobs in Toronto, ON?

For Python Llm jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Python Llm jobs in Toronto, ON look for?

The top searched job categories for Python Llm jobs in Toronto, ON are:

Python Llm jobs near you

Senior Generative AI Engineer

Inizio Partners

Toronto, ON

Full-time

Re-posted 17 days ago

Job description

Senior Generative AI EngineerBackground

We are looking for a Senior Generative AI Engineer to design, build, and ship production-grade Generative AI and Agentic AI applications that delivery business value across the organization. This role is focused on building AI applications and services at scale. You will be responsible for building robust, secure, and highly scalable systems that integrate with leading cloud-based AI services.

You will work alongside product managers, designers, and other engineers as an individual contributor. You are expected to own features end-to-end, and to deliver high-quality, reusable code that scales beyond a single use case.

Key ResponsibilitiesSoftware Engineering and Execution
  • Design, build, and ship production-grade Generative and Agentic AI features and applications
  • Own features end-to-end from technical design through implementation, testing, deployment and operation
  • Build reusable, well-abstracted components and shared utilities (e.g., RAG building blocks, agent scaffolding, evaluation harnesses, prompt utilities) to enable faster delivery of future Generative and Agentic AI products
  • Build multi-agent systems using frameworks such as LangChain, LangGraph, Claude Agent SDK and Google ADK
  • Integrate with leading LLM and foundation model APIs, including Azure OpenAI, Google Vertex AI, and AWS Bedrock
  • Build Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking
  • Build clean, well-tested RESTful and/or gRPC APIs with a focus on reliability, security, and performance
  • Implement observability, tracing, evaluation, guardrails for Generative and Agentic AI applications
  • Deploy and operate services on major cloud providers (e.g., GCP, AWS, and Azure) leveraging managed services
  • Participate actively in code reviews and design discussions, sharing knowledge with peers
Required Qualifications
  • 5-7 years of professional software engineering experience with at least 3 years of experience building AI/ML software products
  • Bachelor's degree in Computer Science or a related field (Master's degree preferred)
  • Strong proficiency in Python, with deep software engineering fundamentals (abstraction, modularity, system design, testing, performance)
  • Hands-on experience building and shipping Generative and Agentic AI applications, including LLM integration, prompt engineering, and/or agentic workflows
  • Practical experience integrating cloud-hosted LLM APIs such as Azure OpenAI, Vertex AI, and/or AWS Bedrock
  • Experience with agent frameworks (e.g., LangChain, LangGraph, Google ADK, Claude Agent SDK) and vector databases (e.g., Pinecone, Weaviate, pgvector, Open Search, AlloyDB)
  • Hands-on experience with Google Cloud Platform (GCP), Amazon Web Services (AWS), or Azure
  • Solid understanding of API design, distributed systems, and cloud-native architecture
  • Track record of taking systems from design through production deployment and operation
Preferred Qualifications
  • Experience with containerization and orchestration (Docker, Kubernetes)
  • Knowledge of Generative AI Risk Management frameworks (NIST RFM)
  • Experience supporting developer platforms or internal tooling