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Junior Machine Learning Compiler Engineer Jobs in Toronto, ON

Socotra, Inc.

Machine Learning Engineer

Toronto, ON · On-site

$118.80 - $148.50/hr

Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world's best transportation solutions. We tackle a wide range of challenges, from pricing and ...

Workday

Senior Machine Learning Engineer

Toronto, ON · On-site

Guide and mentor junior engineers, conduct code and architecture reviews, and help shape the ... Deep hands-on experience with industry-standard machine learning and deep learning libraries (e.g ...

Sobeys

Machine Learning Engineer

Toronto, ON · On-site

$120 - $160/hr

Job Title : Machine Learning Engineer Location : Sobeys COLAB Office (Toronto Downtown) Team ... Having experience leading AI/ML projects or mentoring junior engineers would be looked at with ...

Traffix

Machine Learning Engineer

Toronto, ON · On-site

$120 - $180/hr

Introduction As a Machine Learning Engineer I at TRAFFIX you will work with your colleagues to support the productization of data models. This involves taking models created by our data science team ...

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Junior Machine Learning Compiler Engineer information

What are typical projects and responsibilities for a Junior Machine Learning Compiler Engineer in a collaborative team setting?

As a Junior Machine Learning Compiler Engineer, you can expect to work on projects that focus on optimizing machine learning models for performance and deployment across various hardware platforms. Typical responsibilities include assisting in developing and debugging compiler passes, implementing optimizations, and contributing to code reviews. You'll frequently collaborate with senior engineers, data scientists, and hardware specialists to ensure that models are efficiently translated and executed. This role offers valuable learning opportunities through hands-on coding, exposure to state-of-the-art ML frameworks, and regular team meetings for knowledge sharing and mentorship.

What does a Junior Machine Learning Compiler Engineer do?

A Junior Machine Learning Compiler Engineer helps design, develop, and optimize compilers for machine learning models. Their work involves translating high-level machine learning code into efficient low-level code that can run on various hardware platforms, such as CPUs, GPUs, or specialized AI chips. They often collaborate with software engineers and data scientists to ensure that machine learning workloads run efficiently and correctly. This role typically involves programming, debugging, and performance tuning, often using languages like C++, Python, and specialized frameworks.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Compiler Engineer, and why are they important?

To thrive as a Junior Machine Learning Compiler Engineer, you need a solid background in computer science fundamentals, programming (especially C++ and Python), and foundational knowledge of machine learning and compiler theory. Familiarity with frameworks and tools such as LLVM, TensorFlow, MLIR, and version control systems is typically required, along with a relevant bachelor’s or master’s degree. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills set standout candidates apart. These skills and qualities are crucial for efficiently optimizing machine learning models for various hardware targets and collaborating on innovative compiler solutions.

What is the difference between Junior Machine Learning Compiler Engineer vs Data Scientist?

AspectJunior Machine Learning Compiler EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Software Engineering, or related field; knowledge of compiler design and ML frameworksBachelor's or higher in Data Science, Statistics, Computer Science, or related field; strong analytical skills
Work EnvironmentSoftware development teams, focusing on compiler optimization for ML modelsData analysis teams, focusing on data interpretation and model development
Employer & Industry UsageTech companies, AI startups, hardware firmsTech firms, finance, healthcare, research institutions

The Junior Machine Learning Compiler Engineer primarily focuses on developing and optimizing compilers for machine learning models, requiring programming and compiler knowledge. In contrast, a Data Scientist analyzes data, builds models, and provides insights. Both roles are essential in AI and tech industries but differ in technical focus and daily tasks.

What are popular job titles related to Junior Machine Learning Compiler Engineer jobs in Toronto, ON? For Junior Machine Learning Compiler Engineer jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning Compiler Engineer jobs in Toronto, ON look for? The top searched job categories for Junior Machine Learning Compiler Engineer jobs in Toronto, ON are:
Junior Machine Learning Compiler Engineer jobs near you
Infographic showing various Junior Machine Learning Compiler Engineer job openings in Toronto, ON as of July 2026, with employment types broken down into 9% As Needed, 89% Full Time, 1% Part Time, and 1% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Machine Learning Engineer (Energy) - MLEEAS

United States Digital Space LLC

Hamilton, ON • On-site

$90 - $120/hr

Other

Posted 12 days ago

Job description

Job Title : Machine Learning Engineer (Energy)Industry

Energy & Utilities

Position Overview

The ML Engineer will develop and deploy machine learning models supporting predictive maintenance, energy demand forecasting, asset optimization, and renewable energy production analytics.

Responsibilities
  • Develop machine learning pipelines.
  • Build predictive analytics solutions.
  • Deploy ML models into production.
  • Optimize model performance and monitoring.
  • Collaborate with data scientists and engineers.
  • Support AI-driven operational excellence programs.
Required Skills
  • Python
  • Machine Learning
  • TensorFlow
  • PyTorch
  • Scikit-Learn
  • Databricks ML
  • Feature Engineering
  • Model Deployment
Preferred Skills
  • Predictive Maintenance
  • Demand Forecasting
  • Energy Load Optimization
  • Renewable Energy Analytics
Mandatory Experience
  • 5+ years in Machine Learning Engineering.
  • Must have prior Energy sector experience.

For more details reach at hr@unitedstatesdigital.space

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