Senior Machine Learning Engineer (Ai)

TL;DR

Senior Machine Learning Engineer (Ai): Taking end-to-end ownership of the machine learning lifecycle from experimentation and model prototyping to deployment and monitoring in production with an accent on optimizing systems for reliability and performance. Focus on delivering customer impact through data and ML, building end-to-end pipelines, and driving reliability practices in deployed models.

Location: Must be located in Canada

Salary: CA$128,000 to CA$160,000

Company

hirify.global is a company that offers accounting software designed for small businesses.

What you will do

• Design, prototype, and validate machine learning models to power product features or internal tools.
• Own and lead all phases of the ML lifecycle from experimentation through to production deployment and model monitoring.
• Collaborate with Data Engineers and Product Engineers to integrate models into production infrastructure.
• Develop and prototype features for the shared feature store, including documentation, versioning, and consistency validation.
• Design experiments and interpret results to guide product and business decisions.
• Contribute to standards and documentation, mentor junior team members, and help shape the evolving ML platform.

Requirements

• 5+ years of experience in data science, applied ML, or ML engineering roles.
• Strong background in supervised and unsupervised learning, statistical modeling, and experimentation techniques.
• Proven experience developing and shipping ML models in production environments.
• Strong Python and SQL skills; comfort working with structured and unstructured data.
• Hands-on experience building and deploying ML or LLM-based systems.
• Familiarity with cloud infrastructure and ML tools, ideally on Google Cloud Platform.
• Deep understanding of end-to-end ML operations including model observability, model drift detection, and model performance optimization.
• Strong communication skills and ability to explain technical concepts to non-technical stakeholders.
• Demonstrated initiative, adaptability, and ability to operate independently on complex problems.

Nice to have

• Experience working with Agentic Models.
• Familiarity with LLM orchestration frameworks.
• A background in software engineering, enabling strong collaboration with infrastructure teams and greater autonomy in full-stack ML delivery.

Culture & Benefits

• Fair market value and internal equity commensurate with experience and specific skill set.