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Hugging Face Jobs in Ontario (NOW HIRING)

Strong proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, and/or Hugging Face. * Deep understanding of machine learning algorithms, statistical modeling, experimental design ...

... the Hugging face ecosystem Background in generative models and fine-tuning of foundation models Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX ...

Strong proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, and/or Hugging Face. * Deep understanding of machine learning algorithms, statistical modeling, experimental design ...

Proficiency in programming languages such as Python and experience with machine learning libraries/frameworks, e.g., PyTorch, scikit-learn, Hugging Face, SQL, graph databases (Neo4j/Cypher, Cosmos DB ...

Strong proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, and/or Hugging Face. * Deep understanding of machine learning algorithms, statistical modeling, experimental design ...

AI Engineer

Toronto, ON

CA$77K - CA$117K/yr

Deep handson experience with leading AI and LLM frameworks, including OpenAI APIs, Anthropic, Hugging Face, and LangGraph, along with a strong understanding of LLMbased application design. * Proven ...

AI Engineer

London, ON

CA$77K - CA$117K/yr

Deep handson experience with leading AI and LLM frameworks, including OpenAI APIs, Anthropic, Hugging Face, and LangGraph, along with a strong understanding of LLMbased application design. * Proven ...

Hugging Face Transformers, prompt engineering, post-training/fine-tuning pipelines, retrieval-augmented generation (RAG), and agentic AI frameworks. Experience with inference optimization and high ...

... Hugging Face and LlamaIndex - Implement and optimize vector search and hybrid search solutions perform model training evaluation and finetuning using techniques such as LoRA and QLoRA - Develop APIs ...

Hands-on experience with frameworks like Hugging Face Transformers, LangChain, or OpenAI APIs * Natural Language Processing (NLP): strong understand of NLP tasks such as entity recognition ...

Strong hands-on experience with both classical ML (GLMs, LightGBM, XGBoost etc ) and modern NLP (BERT, embeddings, LLMs, Hugging Face, RAG) for modelling both structured & unstructured datasets ...

AI Engineer

Markham, ON

CA$77K - CA$117K/yr

Deep handson experience with leading AI and LLM frameworks, including OpenAI APIs, Anthropic, Hugging Face, and LangGraph, along with a strong understanding of LLMbased application design. * Proven ...

Proficiency in programming languages such as Python and experience with machine learning libraries/frameworks, e.g., PyTorch, scikit-learn, Hugging Face, SQL, graph databases (Neo4j/Cypher, Cosmos DB ...

Hands-on experience with frameworks like Hugging Face Transformers, LangChain, or OpenAI APIs * Natural Language Processing (NLP): strong understand of NLP tasks such as entity recognition ...

Showing results 21-40

Hugging Face information

What is the difference between Hugging Face vs Machine Learning Engineer?

AspectHugging FaceMachine Learning Engineer
Required CredentialsTypically requires knowledge of NLP, deep learning, and Python; certifications are optionalRequires degrees in CS or related fields; experience with ML frameworks; certifications beneficial
Work EnvironmentCollaborative, research-focused, often in tech companies or startupsDevelopment, deployment, and optimization of ML models in various industries
Employer & Industry UsageUsed by AI/ML companies, research labs, and open-source communitiesEmployed across tech, finance, healthcare, and other sectors implementing ML solutions

Hugging Face primarily focuses on NLP tools, libraries, and open-source models, serving as a platform for AI research and development. Machine Learning Engineers develop, implement, and optimize ML models across various domains. While Hugging Face offers resources and tools that ML Engineers use, the roles differ: Hugging Face is a platform, whereas Machine Learning Engineer is a job role involving hands-on model development and deployment.

What are popular job titles related to Hugging Face jobs in Ontario? For Hugging Face jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Hugging Face jobs in Ontario look for? The top searched job categories for Hugging Face jobs in Ontario are:
Infographic showing various Hugging Face job openings in Ontario as of August 2026, with employment types broken down into 69% Full Time, 29% Part Time, and 2% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.

Lead Data Scientist - AgenticAI

MCKESSON

Mississauga, ON • On-site, Remote

Full-time

Re-posted 5 days ago


McKesson rating

7.9

Company rating: 7.9 out of 10

Based on 209 frontline employees who took The Breakroom Quiz

47th of 86 rated pharmaceutical


Job description

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.

McKesson Corporation is seeking a highly skilled and innovative Lead Data Scientist with experience on Generative AI development. This role will lead the design, development, and deployment of cutting-edge ML & GenAI solutions, leveraging advanced machine learning techniques to solve complex healthcare challenges and drive business transformation.

Job Responsibilities

  • Lead the end-to-end lifecycle of Generative AI and agentic AI solutions, including ideation, research, prototyping, implementation, evaluation, deployment, and production support.
  • Architect and develop scalable GenAI systems such as LLM-based applications, Retrieval-Augmented Generation (RAG), AI agents, and intelligent automation workflows to improve decision-making, operational efficiency, and customer outcomes.
  • Drive adoption of best practices in prompt engineering, LLM evaluation, fine-tuning strategies, and secure model hosting where applicable.
  • Apply advanced data science and machine learning techniques across a wide range of use cases including predictive modeling, forecasting, classification, anomaly detection, recommendation systems, NLP, and GenAI-enabled analytics.
  • Develop custom ML models and analytical frameworks tailored to complex healthcare and enterprise data challenges.
  • Perform exploratory data analysis (EDA), feature engineering, and statistical analysis to generate actionable insights and guide solution design.
  • Collaborate with engineering and platform teams to deploy, monitor, and maintain ML and GenAI solutions in production environments using cloud-native and MLOps best practices.
  • Establish model performance tracking, drift detection, reliability monitoring, and continuous improvement processes for deployed models and AI agents.
  • Ensure solutions are scalable, cost-efficient, resilient, and aligned with enterprise architecture standards
  • Ensure strong model governance, documentation, and auditability across all ML and GenAI solutions.
  • Apply Responsible AI principles including explainability, transparency, data privacy, security, and regulatory compliance, particularly within healthcare contexts.
  • Provide guidance on safe, compliant, and ethical use of LLMs and agentic AI across enterprise use cases.
  • Work closely with business stakeholders and product managers to translate requirements into clear analytical problem statements, solution designs, and execution roadmaps.
  • Present technical solutions, insights, and progress updates to both technical and non-technical audiences, including senior leadership.
  • Mentor and guide junior data scientists and engineers, fostering a culture of technical excellence, innovation, and continuous learning.

Job Qualifications

  • Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or a related quantitative field.
  • 7 -10+ years of experience in data science or advanced analytics, with significant hands-on experience in Generative AI and LLM-based systems.
  • Proven experience designing, building, and deploying production-grade ML and GenAI solutions, including LLMs, RAG architectures, and AI-driven automation.
  • Strong proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, and/or Hugging Face.
  • Deep understanding of machine learning algorithms, statistical modeling, experimental design, and data structures.
  • Experience working with cloud platforms (Azure preferred; AWS/GCP acceptable) and MLOps practices.
  • Ability to clearly communicate complex technical concepts to diverse business and technical audiences.
  • Demonstrated leadership in driving projects, influencing stakeholders, and mentoring team members.

Working Conditions:

  • In office requirement, we are Flex and Connect with 2 days a week in office

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.

Our Base Pay Range for this position

$122,100 - $162,800

McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:
McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.


McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.

McKesson job postings are posted on our career site: careers.mckesson.com.

McKesson is an Equal Opportunity Employer

McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.

McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) Disability_Accommodation@McKesson.com or (Canada) Accessibility@mckesson.ca. Resumes or CVs submitted to this email box will not be accepted.

Join us at McKesson!


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