Senior Machine Learning Engineer

TL;DR

Senior Machine Learning Engineer (AI): Develop end-to-end ML/AI applications and infrastructure to enhance safety, efficiency, and sustainability of physical operations with an accent on scalable ML infrastructure, real-time and batch model deployment, and cross-functional collaboration. Focus on designing innovative ML products, leading zero-to-one initiatives, and bridging ML science with engineering teams.

Location: Remote, must reside in Canada

Salary: 132,600–171,600 CAD annually

Company

hirify.global is a pioneer of the Connected Operations™ Cloud platform, enabling organizations to harness IoT data to improve safety, efficiency, and sustainability across industries such as agriculture, construction, transportation, and manufacturing.

What you will do

• Design and build ML infrastructure for batch and real-time customer-facing models.
• Lead zero-to-one ML/AI product initiatives from concept to delivery.
• Bridge ML scientists and engineering teams to enable cross-functional project success.
• Drive ML operations improvements, enhancing scalability and efficiency of inference platforms.
• Champion hirify.global’s cultural principles and contribute to global scaling efforts.

Requirements

• Must reside in Canada to be eligible for this remote role.
• 5+ years experience as a Machine Learning Engineer, Applied Scientist, or similar role.
• BS or MS in Computer Science or quantitative field.
• Proficiency in Python, Java, C++, or Golang and ML frameworks like PyTorch, TensorFlow, Spark.
• Experience with end-to-end ML application development and understanding of ML algorithms.

Nice to have

• Experience leading small cross-functional teams delivering ML experiences.
• Experience building zero-to-one ML applications.

Culture & Benefits

• Competitive total compensation including base salary, bonus, and RSUs.
• Employee-led remote and flexible working arrangements.
• Health benefits and inclusive work environment.
• Support for accommodations during recruiting process.
• Flexible working model supporting remote, hybrid, and onsite preferences.