Build and productionize LLM and NLP models across various tasks
Improve model accuracy, relevance, and robustness through evaluation frameworks and experimentation
Design scalable ML services and inference pipelines in Python
Integrate models with retrieval systems and feature stores
Collaborate with Product, Engineering, and Applied Sciences to translate requirements into engineering plans
Participate in technical design reviews and mentor on NLP techniques

Requirements

4+ years applying ML in production with depth in NLP, LLM workflows, embeddings, or retrieval augmented systems.
Hands-on experience with transformer models and fine-tuned LLMs for reasoning and generation tasks.
Strong proficiency in Python, PyTorch or TensorFlow, and API/microservice development.
Experience in scalable and reliable ML services focusing on testing and deployment patterns.
Ability to design components with control flow and state management.
Strong collaboration skills with cross-functional partners.

Benefits

Health and wellness benefits starting day 1️⃣
Equipment setup with MacBook and budget for home office
Monthly phone and internet subsidy
Professional mastery allowance for learning support
Flexible co-working locations in Ontario and BC
Supportive culture with opportunities for connections in a remote-first environment
Opportunities for participation in townhalls and AMA
Employee Resource Groups for year-round connection
Celebrations for big wins and milestones

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningnatural language processinglarge language modelstransformer modelsembeddingsretrieval augmented systemsPythonPyTorchTensorFlowAPI development

Soft Skills

collaborationmentoringcommunicationtechnical design review