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Google Machine Learning Engineer Jobs in Ontario

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$105K - CA$125K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Required Skills Azure data factory, Azure data bricks, Azure Machine Learning, PySpark, SQL, Python, PB, AWS, SF, DEVOPS and Azure Security - Create and maintain optimal data pipeline architecture ...

Senior Machine Learning Engineer

Mississauga, ON · On-site

CA$105K - CA$125K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Required Skills Azure data factory, Azure data bricks, Azure Machine Learning, PySpark, SQL, Python, PB, AWS, SF, DEVOPS and Azure Security - Create and maintain optimal data pipeline architecture ...

Your Role As an AI / Machine Learning Engineer at Thri5, you'll help build the agent layer that powers our System of Actions. You'll design and implement multi-agent Co-pilot systems that orchestrate ...

The Lead, AI/Machine Learning Engineer will join the AI Delivery and Innovation team within the ... Experience with agent frameworks, such as Microsoft Agent Framework or Google ADK, and agentic ...

$110 - $170/hr

The Product Operations machine learning team is seeking a machine learning research engineer to conduct research in anomaly detection and automated machine learning to address domain-specific ...

Showing results 41-60

Google Machine Learning Engineer information

See Ontario salary details

$25.5K

$137.3K

$223.5K

How much do google machine learning engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for google machine learning engineer in Ontario is $137,346.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,500.00 and $170,500.00 per year, depending on experience, location, and employer.

What skills and qualifications are needed to thrive as a Google machine learning engineer?

To thrive as a Google Machine Learning Engineer, you need strong expertise in mathematics, statistics, programming (especially Python or C++), and a solid background in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms (like Google Cloud), and advanced certifications can be highly beneficial. Excellent problem-solving, teamwork, and communication skills help you collaborate across teams and explain complex models to stakeholders. These skills are essential to driving innovation, building scalable solutions, and ensuring impactful results in a fast-paced, research-driven environment.

What is a Google machine learning engineer?

A Google Machine Learning Engineer designs, builds, and optimizes machine learning models to improve Google's products and services. They work with large datasets, implement algorithms, and deploy scalable AI systems. Collaboration with data scientists, software engineers, and product teams is essential to integrate models into real-world applications. Strong knowledge of Python, TensorFlow, and cloud computing is often required. This role focuses on both research and practical implementation to enhance automation and decision-making across Google products.

What types of projects and collaborations can Google machine learning engineers expect to be involved in?

Google Machine Learning Engineers often contribute to diverse projects, such as developing next-generation search algorithms, optimizing user experiences across products, or creating scalable machine learning systems for internal and external clients. The role frequently involves collaborating with data scientists, product managers, software engineers, and researchers to define project goals and deliver impactful solutions. You can expect to participate in code reviews, prototype new models, and provide expert input during technical discussions. This collaborative, interdisciplinary approach ensures innovative outcomes and offers ongoing opportunities for professional growth and skill development.

What are popular job titles related to Google Machine Learning Engineer jobs in Ontario?

For Google Machine Learning Engineer jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Google Machine Learning Engineer jobs in Ontario look for?

The top searched job categories for Google Machine Learning Engineer jobs in Ontario are:

Infographic showing various Google Machine Learning Engineer job openings in Ontario as of August 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Hybrid job distribution, with an average salary of $137,346 per year, or $66 per hour.

Machine Learning Engineer, Lyft Business & Ads

Lyft

Toronto, ON • On-site

Full-time

Medical, Dental, Life, Retirement, PTO

Re-posted 9 days ago


Lyft rating

7.6

Company rating: 7.6 out of 10

Based on 33 frontline employees who took The Breakroom Quiz

2nd of 9 rated taxi private hire


Job description

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Machine Learning is at the heart of Lyft's products and decision-making. 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 marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust.

Lyft Business builds products that help organizations move the people who matter most-employees, customers, patients, and guests-easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs.

We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions.

This role is ideal for someone who is technically versatile, energized by variety, and wants to see their work directly shape a large-scale business.

Responsibilities:
  • Develop and deploy ML models across multiple problem domains - including dynamic pricing, marketplace optimization, fraud detection, and anomaly/behavior detection - in production environments serving millions of rides
  • Build and iterate on agentic AI systems (e.g., LLM-powered analytical agents) that automate decision-making and reduce operational overhead
  • Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform
  • Partner with Data Scientists on the Algorithms and Decisions teams to take research prototypes from proof-of-concept to production at scale
  • Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement
  • Identify new opportunities where ML can create leverage across Lyft Business verticals (Healthcare, Lyft Pass, Business Travel) and pitch solutions
  • Contribute to team engineering standards - code quality, observability, documentation, and testing practices
Experience:
  • Experience with GenAI / LLM ecosystems - prompt engineering, RAG, agent frameworks (e.g., LangChain, LangGraph), or fine-tuning
  • Exposure to graph-based ML methods (graph neural networks, knowledge graphs, network analysis)
  • Experience with pricing, marketplace, or fraud-related ML problems
  • Familiarity with cloud ML services (AWS SageMaker, Bedrock) or internal ML platforms
  • Track record of identifying and scoping ML projects independently, not just executing on pre-defined specs
Benefits:
  • Extended health and dental coverage options, along with life insurance and disability benefits
  • Mental health benefits
  • Family building benefits
  • Child care and pet benefits
  • Access to a Lyft funded Health Care Savings Account
  • RRSP plan with company match to help save for your future
  • In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
  • Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
  • Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule - Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $118,800 - CAD $148,500, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.


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About Lyft

Sourced by ZipRecruiter

At Lyft, our mission is to improve people's lives with the world's best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Industry

Ground public transportation

Company size

5,001 - 10,000 Employees

Headquarters location

San Francisco, CA, US

Year founded

2012

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