Experienced Ordnance Specialist in Canada

About the Team U.S. businesses spend over $100 billion annually on food for employees and customers. DoorDash for Business is a standalone vertical within DoorDash, focused on building meal procurement solutions for companies. DoorDash for Business uses DoorDash's global marketplace, selection, and infrastructure, to offer a compelling enterprise offering to employers at Fortune 1000 companies. As the Manager, Enterprise Sales, you will lead a team of Enterprise Account Executives who are responsible for acquiring new Enterprise customers in the US. You will partner with marketing, finance, legal, sales operations, and product to build your strategy. About the Role You will be responsible for managing a team of ~8 Enterprise Account Executives and help them build pipeline and drive net new customer acquisition strategies across the US. Additionally, you will be a key driver for one of DoorDash’s growth verticals and have the ability to grow your team and career. As such, you’ll be in a high impact role where you’ll work extensively with cross-functional teams to execute on growth and operational initiatives. Working alongside large to mid-size brands, you’ll have the opportunity to shape the future of DoorDash’s Enterprise business. You will report to the Director, Pre-Sales, DoorDash for Business to work on a strategy and hit revenue targets. We are looking for a sales professional who can coach and develop talent, hire and help to win business. You have experience with SaaS platform products, leadership, sales, forecasting and building prospecting strategies. You’re excited about this opportunity because you will… Lead: Lead a team of Enterprise Account Executives that attract new Enterprise customers, while taking a people first approach to attract outstanding talent and support the personal development of members in your organization. Build: You'll have your fingerprints all over DoorDash's next big business. You'll use your curiosity and other skill

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Senior Data Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. This is a hybrid position and you must be located in Sunnyvale, San Francisco, or Seattle. You're excited about this opportunity because you will... Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because... 5+ years of professional experience 3+ years experience working in data engineering, business intelligence, or a similar role Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms Excellent communication skills and experience working with technical and non-tec

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Lead DFT Engineer Job Description: Developing silicon for edge-to-cloud computing isn't just about speed; it’s about balancing high-performance data processing with extreme power efficiency and reliability in remote environments. As the Design for Test (DFT) Lead, you will be the architect of our testing strategy, ensuring our data center chips are flawlessly manufacturable and resilient enough for edge deployment. Key Responsibilities: Architectural Leadership: Define and implement the end-to-end DFT architecture for complex SoCs, including Hierarchical DFT, Scan compression, Boundary Scan and MBIST. Edge-Specific Reliability: Develop strategies for In-System Test (IST) and power-on self-test (POST) to ensure chip health in remote edge data centers. Implementation & Flow: Oversee scan insertion, ATPG (Stuck-at, Transition, Path Delay), and Memory /Logic BIST. Cross-Functional Synergy: Collaborate with Design, Physical Design, and Yield teams to ensure high test coverage while minimizing area overhead and power impact as well as timing analysis . Post-Silicon Validation: Lead the bring-up and debug phase on ATE (Automated Test Equipment) to root-cause silicon failures and optimize test time. Technical Requirements: Experience: 12+ years in DFT, with at least 2 years in a leadership or principal role. Bachelor’s degree in a related field. Tools:

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. Datastores Engineer, Platform Infrastructure The Auth0 platform secures more than 100 million logins each day for customers all around the world - and we're growing fast! The Platform Infrastructure team enables Auth0 engineers to move faster by giving them tools to easily deploy and manage their services on AWS and Azure. This is a role with a huge impact. You will get to work with engineers throughout the organization and what you build will be a foundational piece of the infrastructure that allows Auth0 to scale for years to come. We are looking for Engineer who are passionate about distributed systems, availability, and delivering customer value to join our Platform Infrastructure Datastores team. Because we build and support the overall Auth0 platform, the ideal candidate is someone who is passionate about infrastructure, operations, databases and not intimidated by cross-organization coordination and collaboration. You will: Develop our large, distributed and highly-available infrastructure. Implement platform tools that allow feature teams to deploy and manage the datastores for their services. Research new technologies to accelerate new environment creation. Carry cross team initiatives from end to end: code reviews, design reviews, operational robustness, security hygiene, etc. Participate in the team's on-call rotation. You might be a good fit if you: Have 5-8 years of software development experience. Are proficient in or have a desire

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Developer Infrastructure org is the engine behind Robinhood's entire engineering organization — a collection of tightly integrated teams whose collective mission is to make every engineer at Robinhood faster, more reliable, and exponentially more productive. The org spans four major teams: DevX (Developer Experience), TestX (Test Infrastructure), Backend Platform, and Mobile Platform. DevX owns Robinhood's monorepo and Bazel-based build infrastructure — the critical layer between a developer writing code and that code being ready to ship — along with the company's full CI/CD pipeline and remote build execution cluster. TestX owns the infrastructure behind Robinhood's entire test experience: the integration test environments, and personal development environments that serve as miniature simulations of the full Robinhood system, giving engineers a safe, isolated space to test their code end-to-end before it ever touches production. Backend Platform and Mobile Platform own the core language runtimes, libraries, IDEs, and developer toolchains across Python, Go, TypeScript, Swift, and Android. Together, these teams share a single north star: leveraging AI and agentic systems

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. Data and analytics are at the heart of Lyft's products and decision-making. The Metrics team sits in the Central Market Management organization and owns the business metrics that leaders use to run the marketplace. We define these metrics, build and manage the tools and dashboards that make them reliable and easy to access, and drive consistent, standardized definitions across the organization. We are looking for a Data Scientist to join the Metrics team and help shape Lyft's products and decision-making. You will own a domain within the team's surface area, building and maintaining the data and metrics that leaders and partner teams rely on, with significant executive exposure along the way. We want an intellectually curious person with strong attention to detail, a track record of analytical problem-solving, and skilled communication. You will report to a Data Science Manager. Responsibilities Own one or more domain datasets end-to-end, from source data through to the metrics that consumers rely on Build and maintain the processing logic and pipelines that turn raw inputs into trusted, analysis-ready data Own the business metrics derived from that data, developing the deep understanding of the source needed to build each metric correctly Ensure the data is accurate, consistent, and reliable, with quality checks that catch problems before consumers see them Deliver data and metrics to stakeholders in a usable form, and support them as they integrate it into their decisions Partner with product managers, engineers, and operators to translate the data into decisions and action Communicate findings to stakeholders in a clear and concise manner Experience Degree in a quantitative field such as statistics, economics, applied math, operations research, or engineering (advanced degrees preferred), or relev

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? This role is for people who love building tools for their coworkers. The Internal Applications team creates tools that help us create better models. In this role you will collaborate with internal stakeholders, which include annotators, ML researchers, product managers and more. Join our team of builders who create tooling that will pave the way for the next generation of large language models! As a Full-Stack Software Engineer on the Internal Applications team, you will: Work with a small talented and enthusiastic team of software engineers Contribute to delightful experiences for our user-facing products, meticulously crafting code for browsers and servers Collaborate and grow with your engineering colleagues of all levels through direct pairing sessions, architectural designs, documentation and talks Identify and remove roadblocks to enable your team to increase its engineering velocity. Build resilient systems that are mission-critical Keep up with the cutting edge and adopt new technologies to improve performance and reliability You may be a good fit if: You have experience shipping products with a large numb

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. Our Infrastructure team is passionate about building software to solve problems at massive scale. We do this often, and when we believe our solution is worth sharing with the community, such as Envoy Proxy , we open source our ideas for the benefit of others. As a Infrastructure Engineer at Lyft, you will run our Production Infrastructure by monitoring system availability and take a holistic view of our platform health. You will build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you will seek opportunities to optimize our systems in order to push our platform forward, anticipating our customers' needs in order to continually improve the platform. You will provide Lyft partner teams with operational support to help them build robust large scale distributed systems. About the Team Data Pipelines is at the heart of all critical data flowing through Lyft supporting hundreds of services that impact millions of drivers and passengers every day. Our team’s mission is to empower Lyft engineers to self-serve in building and maintaining data pipelines as needed to support products that deliver the world’s best transportation experience. We leverage a variety of technologies to store, stream and manage data making it available to our internal customers. Responsibilities: Maintain and analyze metrics from; operating systems; control planes; and applications to assist in fault detection and performance enhancement Design, develop and deploy tooling and systems that continually improve the reliability, scalability and efficiency of our platform Balance feature development speed and reliability with service-level objectives Operate and improve our Infrastructure using industry best practices and tools Participate in design and

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

Chez Lyft, notre mission est de servir et de connecter. Nous visons à y parvenir en cultivant un environnement de travail où tous les membres de l'équipe ont leur place et peuvent s'épanouir. Les stagiaires travaillent côte à côte avec les meilleurs ingénieurs de l'industrie tout en ayant une autonomie dès le départ. Ils contribuent aux produits destinés aux utilisateurs et peuvent voir leur travail être mis en ligne rapidement. Lyft favorise un environnement collaboratif au bureau, donc il y a toujours un esprit vif désireux d'entendre parler de votre prochaine idée. Alors, quelle est la vôtre? Responsabilités: Prenez en charge votre projet, tout en échangeant avec les autres membres de l'équipe tout au long de la journée pour poser des questions et faire le point Vous laissez le code dans un meilleur état que vous ne l'avez trouvé (refactorisation progressive) Vous accordez de l'importance à la fiabilité, garantie par les tests (tests unitaires, d'intégration et de charge) Participez aux revues de code afin d'assurer la qualité du code et de partager les connaissances Intégration et déploiement continus Rentrez chez vous en sachant que votre travail d'aujourd'hui améliore concrètement la vie de chaque chauffeur et chaque passager Lyft Expérience: Poursuit actuellement un baccalauréat ou une maîtrise en informatique dans une université canadienne (obligatoire) , avec une date de graduation prévue entre décembre 2027 et l'été 2028 (obligatoire) . Pour les candidats à la maîtrise ayant travaillé entre leur baccalauréat et leur maîtrise : les candidats doivent également avoir moins de 2 ans d'expérience de travail à temps plein pertinente Disponible pendant l'été 2027 pour le stage à Montréal Solides connaissances des fondamentaux de l'informatique Excellentes compétences en communication Passion pour la communauté, la durabilité et/ou le transport Capacité à s'épanouir dans un environnement d'entreprise en démarrage (startup) Contributio

Chez Lyft, notre raison d'être est de servir et de connecter. Nous visons à y parvenir en cultivant un environnement de travail où tous les membres de l'équipe ont leur place et peuvent s'épanouir. En tant que stagiaire en automatisation des tests chez Lyft, vous collaborerez étroitement avec des ingénieurs chefs de file dans l'industrie, tout en bénéficiant de la liberté d'innover dès le premier jour. Vos contributions seront essentielles pour accélérer le développement de nos produits et renforcer la confiance et la satisfaction des utilisateurs grâce à la création d'outils d'automatisation de tests à la fine pointe de la technologie. Chez Lyft, nous cultivons un environnement de bureau dynamique et collaboratif, où des esprits brillants sont toujours prêts à écouter et à soutenir votre prochaine grande idée. Quelle sera la vôtre? Responsabilités: Prenez en charge votre projet, tout en échangeant avec les autres membres de l'équipe tout au long de la journée pour poser des questions et faire le point Vous laissez le code dans un meilleur état que vous ne l'avez trouvé (refactorisation progressive) Vous accordez de l'importance à la fiabilité, garantie par les tests (tests unitaires, d'intégration et de charge) Participez aux revues de code afin d'assurer la qualité du code et de partager les connaissances Intégration et déploiement continus Rentrez chez vous en sachant que votre travail d'aujourd'hui améliore concrètement la qualité de vie de chaque usager de Lyft Urban Solutions ! Expérience: Poursuit actuellement un baccalauréat ou une maîtrise en informatique dans une université canadienne (obligatoire) , avec une date de graduation prévue entre décembre 2027 et l'été 2028 (obligatoire) . Pour les candidats à la maîtrise ayant travaillé entre leur baccalauréat et leur maîtrise : les candidats doivent également avoir moins de 2 ans d'expérience de travail à temps plein pertinente Disponible pendant l'été 2027 pour le stage à Montréal Solides connaissances des fo

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. We're looking for a Workato/Boomi Integration Engineer to build and support enterprise automation, with a focus on Legal systems integration (CLM, e-signature, matter management, compliance). You'll work across iPaaS, APIs, and AI/agentic tooling (Workato Genie, AI Skills, MCP servers) to connect Legal and other business systems. Responsibilities: Design and build Recipes and process automations across multiple systems, including AI-powered workflows using Workato Genie and MCP servers. Build and support AI Agents (Genies) for Legal and business-process automation, including prompt design and IDP for unstructured Legal content (contracts, filings). Design and manage secure API endpoints (REST/SOAP) and SFTP connections; build ETL/data-sync pipelines across formats (JSON, XML, CSV, EDI). Deploy and manage On-Premises Agents (OPA) for secure, behind-firewall connectivity. Maintain platform environments and security (RBAC, SSO, versioning); monitor jobs and troubleshoot failures. Build employee-facing tools (Workbot/ChatOps, Workflow/AgentX Apps, Slack integrations) with human-in-the-loop steps. Integrate business applications (CRM, HR, Finance, LMS, Legal, Budget & Forecast) via Boomi, with emphasis on Legal, Financial, and Supply Chain integrations. Write and optimize SQL/PL-SQL and custom scripts (Java/Groovy/JavaScript/Python); manage code via Git/GitHub; provide production support and on-call as needed. Partner with Legal, Compliance, and IT stakeholders to gather requirements and translate them into working integrations. Experience: 6–8 years of integration/automation experience, with hands-on Workato and Boomi. 4–6 years building and managing APIs (API Gateway, OAuth/SAML/JWT) and SFTP-based file transfers. 2+ years supporting Legal systems integrations (CLM, e-signature, matter management, c

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 Bikes & Scooters team is developing the future of micro-mobility and we are looking for a Mechanical Engineer to come in and help drive the development of our newest vehicles and sustain our fleet in operation. Responsibilities: Drive design decision by collaborating with product, engineering (EE/ME/FW/SW), reliability, and systems engineering teams Lead post-launch sustaining activities intended to support a smooth transition into production while maintaining high quality standards Derive technical architecture and engineering specifications from product requirements Use analysis to support engineering designs Lead sustaining and continuous improvement projects from concept through release and into field operations Work with GSM and Manufacturing teams to vet supply chain and production partners Prototype; create quick experimental mock-ups and meticulous mechanical models Research technologies and scope development opportunities Develop CAD databases and drawing packages, and drive handoff to manufacturers Support the build and test product development cycle, travel required Test failure analysis and solution validation to complete successful product development Conduct field failure analysis and solution evaluation Lead large projects from idea to positive execution Act on feedback to learn and grow Effectively communicate across cross functional teams to achieve results Experience: BS or MS degree in Mechanical Engineering or related technical field, and 5+ years of related industry experience Experience leading the development of a feature or module of a consumer product Strong foundation in mechanical engineering fundamentals, including solid mechanics, electromagnetics, thermodynamics, and knowledge of basic engineering materials and manufacturing processes Experience in perfo

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Tokenization team's mission is to bring both public and private equity to be tradable 24/7 on decentralized exchanges (DEXs) across the Robinhood Chain. We work at the intersection of blockchain technology, financial market infrastructure, and modern distributed systems - with a focus on accessibility, security, and scalability. Equity markets have been closed nights and weekends for a century; we're building the infrastructure that changes that. As a Software Engineer , you'll build and own backend services that make tokenized equities work end to end - issuance, custody, and settlement on-chain, kept in sync with traditional brokerage and ledger systems. You'll ship product-facing features and platform capabilities in a domain where correctness is non-negotiable - the systems you build move real customer assets, continuously, around the clock. This role is based in our Toronto, ON office(s), with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-perfor

About the Role We are a small team of AI builders in Paytm Labs. As a Staff AI Platform Engineer, you will work across inference and agentic systems. You will contribute to Paytm's AI inference platform (Pi), serving internal teams and enterprise customers - running our own coding and domain-specific models (voice, vision, risk, fintech workflows) as well as third-party models. You will also architect and build the platform that enables autonomous AI agents to operate safely and reliably in production - the runtime, orchestration, and developer tooling for agents to reason, plan, use tools, and execute complex multi-step workflows, automating both software development and business processes. You will work at the intersection of LLMs, distributed systems, and production fintech infrastructure, helping define how inference and agentic AI are built and deployed across payments, risk, fraud, collections, support, and developer experience.