Jobs in Canada

Software Development Engineer Iii Data in Toronto

155 active opportunities · Updated October 2026

Explore current software development engineer iii data jobs in Toronto. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Toronto, Ontario, Canada· Full-time
✓ High-confidence listingCompany trend -63.6%

C$108K – C$135K/yr

Quick readStrong listing-quality and freshness signals

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. This is a contract position through our staffing partner Magnit. 108,000.00 - 135,000.00 - 162,000.00 CAD Annual This role is not eligible for the Okta-sponsored benefits listed below. Magnit will provide any locally required benefits. Okta seeks a skilled Senior Recruiter to drive full-lifecycle recruitment and build strategic talent pipelines for our Engineering organization across North America. As part of our AMER Tech Recruiting team, you will be a trusted talent advisor responsible for sourcing, engaging, and delivering top-tier engineering talent while maintaining an "always recruiting" mindset in a fast-paced, high-growth environment. What You'll Be Doing Own full-lifecycle recruitment for Engineering and technical roles (Software Engineering, Site Reliability, Security, TPM, Product) across US & Canada, managing a flexible req load that scales with business priorities. Partner strategically with hiring managers and leadership to understand talent needs, define role scope, advise on talent gap mitigation, and challenge assumptions to ensure hiring decisions strengthen long-term organizational capability. Build and execute talent strategies that balance external hiring with internal mobility, creating sustainable pipelines that reflect commitment to diversity, inclusion, and high-performing engineering culture. Drive metrics-informed recruiting decisions by developing KPIs, analyzing recruiting data, and using insights to optimi

AWSRestMachine LearningAI
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$45/hr

Quick readStrong listing-quality and freshness signals

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. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

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L
📍 Toronto, Canada
✓ Quality checkedCompany trend -72.4%

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. The Rider Loyalty team is where riders become members. We build the membership, rewards, and benefits products that give people a reason to choose Lyft on every trip, and we make sure the value a rider has earned shows up at the moment it matters. Loyalty sits inside the Rider Loyalty, Partnerships, and Rider Pay (PLP) group. You will lead a team of engineers across iOS, Android, and Server. You will own the membership and rewards platform end to end and work daily with Product, Design, Data Science, and Partnerships. Responsibilities: Own the Loyalty roadmap from strategy through delivery. Turn goals like member growth and retention into an engineering plan, and manage the dependencies that run through Partnerships and Rider Pay. Build and scale the systems behind membership, rewards earning and redemption, and benefit delivery. Hold a high technical bar through architecture reviews, tech debt management, observability, reliability, and on-call. Grow engineers by matching people to the right opportunities, setting clear expectations, and giving feedback early. Experience: 5+ years building software professionally, including 2+ years directly managing engineers. You have managed a team that shipped both mobile and backend work, and you can still read and review code in at least one of those areas. You have owned a consumer product used by millions of people each month. You use AI tools in your own work and have a clear view of where they help and where they do not. BS/MS in Computer Science, Computer Engineering, or a related field, or equivalent practical experience. 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 Accou

Artificial IntelligenceAI
O
📍 Toronto, Ontario, Canada· Full-time
✓ High-confidence listingCompany trend -63.6%

From C$146K/yr

Quick readStrong listing-quality and freshness signals

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Engineering Opportunity Reporting to the Director of Quality & Performance, this role as Engineering Manager of Performance & Resilience will drive performance and resiliency improvements for the Auth0 product at Okta. Here you'll be working with some of the most advanced technology in the space, helping to streamline and secure billions of access requests a year. In this role, you will work closely with architects, platform team members, and product engineers to build the testing infrastructure that keeps Auth0 performant at scale — including the frameworks, tooling, and realistic datasets that make that testing meaningful. The ideal candidate is passionate about software quality and architecture, a self-starter, intellectually curious, and brings deep experience with performance testing, load testing frameworks, dataset generation, performance analysis, monitoring tooling, and chaos engineering. What you’ll be doing Collaborate with architects, tech lead, product owners, security and operations engineers to implement best practices related to performance and resiliency Communicate and organize cross-team projects with high business

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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$118.8K/yr

Quick readStrong listing-quality and freshness signals

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 th

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