Jobs in Canada

Customs Associate in Canada

50 active opportunities · Updated October 2026

Explore current customs associate jobs across Canada. Filter by work mode, employment type, experience, department, date posted and distance.

PE
📍 Palo Alto, CA· Full-time· Hybrid
✓ Quality checked

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Are you passionate about engineering quality, performance, and increasing the impact of engineers around you? Software Engineers at Palantir build software at scale to transform how organizations around the world use data. As an engineer within Palantir’s Foundations organization, you’ll have the opportunity to grow more quickly than you ever imagined, as you build the shared infrastructure that underpins the Palantir Foundry, Palantir Gotham, and Palantir Apollo platforms, and drive investments to improve the velocity and quality of our engineering. Teams within Palantir’s Foundations organization are made up of a small number of engineers, each focused on one of four major categories of our infrastructure: • Backend Infrastructure: Maximizes the productivity of our backend developers and ensures Palantir’s platforms have performant and consistent RESTful services. Think: making the “easy way” the “right way” when developing backend services, including designing infrastructure to build hundreds of micro-service repos performantly, or to ensure we keep reliable audit logs of everything users do in our platforms. • Developer Infrastructure: Operates the systems and services that underpin all aspects of our developer ecosystem, including off-the-shelf tooling like GitHub and custom tooling for managing automated changes across hundreds of repositories. • Frontend Infrastructure: Maximizes frontend developer productivity across the entire frontend development stack, from the developer experience in the IDE to the final user experience in the browser. Think: the core infrastructure required to develop and serve our frontends (including features flags, int

TypeScriptJavaReactGit
PE
📍 Palo Alto, CA· Full-time
✓ Quality checked

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Palantir builds applications that help customers organize, understand, and make decisions based on their data. Because these applications serve different roles within an organization's workflow, users frequently have multiple applications open at once, and expect them to work together seamlessly. While backend services handle much of this coordination, delivering a truly fast and responsive experience requires applications to also directly interact with each other through client-side frameworks running in the browser. Building these frameworks is uniquely challenging: every Palantir application plays a distinct role and has its own set of first-class UX concepts, yet the frameworks need to integrate cleanly into all of them. Success requires both strong API design skills and a keen eye for user experience. The frontend frameworks our team builds serve a variety of functions across Palantir's application ecosystem. Some frameworks integrate deeply with the Palantir Ontology—a foundational layer that provides a schema for defining objects and relationships between them. These frameworks enable real-time data synchronization across applications: for example, when a user selects an Ontology object on a map, data plots in a different application instantly update to show that object's properties. Other frameworks operate independently of the Ontology: for example, one framework allows applications to define custom behaviors that can be invoked by other applications or even by AI agents, giving them the flexibility to expose arbitrary functionality across the platform. Core Responsibilities As a software engineer on this team, you'll work with these cross-ap

L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -72.4%
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 Business is changing the way companies, brands and organizations leverage the Lyft platform to redefine the way they operate and move people around. We are solving big problems, and meeting the needs of our clients and the people they care about in a whole new way. We realize that the world has changed so much recently, and that the needs of our customers and how they envision transportation is changing too. Our work is fun, challenging and rewarding and we are looking for customer and growth-focused team members passionate about solving problems and delighting our customers. As an Account Manager, you’ll help our clients understand the power of Lyft Business. You will build and manage a named account list of large organizations in the US, ensuring that they leverage Lyft’s products for any transportation objective they have. We’re building the next great transportation platform, and we need world-class talent and candidates that aren’t afraid to try new things and think outside the box to build new business. Responsibilities: Own the customer relationship with enterprise grade partners as their primary representative to Lyft for all their business related transportation needs Partner with Fortune 500 companies, to design, sell and implement custom transportation solutions for their respective passengers that include employees (essential and non), recruits, VIPs, guests, subscribers, etc Identify and generate additional revenue streams within existing accounts, including up-sells and cross-sells; selling across commuter benefits, events, employee perks, concierge, and corporate travel use cases to exceed revenue targets Generate and maintain an active pipeline with meticulous attention to opportunity staging, close dates, revenue forecasts, and deal documentation Constantly ‘se

L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -72.4%
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. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes Drive collaboration and coordination with cross-functional teams

PythonMachine LearningAIGo
L
📍 San Francisco, CA· Full-time
✓ High-confidence listingCompany trend -72.4%
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. The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.&n

PythonMachine LearningAIGo
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