Python Developer in Canada

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role We are hiring a Firmware Validation & Integration Engineer for our autonomy software team. This is a critical role to build robust and scalable validation for our firmware and systems to ensure reliability at every level. In this role, you will work with our electrical, firmware, and autonomy engineers to build the infrastructure and test suites required to validate the system. This includes designing and implementing our Hardware-in-the-Loop (HIL) simulation environments and automation frameworks from the ground up. You will report to the Autonomy Platform Lead on our Autonomy Platform Team at DoorDash Labs. We expect this role to be hybrid with some time in-office and some time remote. You’re excited about this opportunity because you will… Play an integral role on a small and focused team. Design and build Hardware-in-the-Loop (HIL) systems to simulate vehicle dynamics and sensor data for comprehensive firmware and system-level validation. Develop automated test infrastructure and software tools to exercise multiple embedded platforms throughout our robot system. Interface many layers of our control system including vehicle controls, power management, and motion control to ensure seamless system integration. Implement low-level test sequences and validation algorithms to safely stress-test vehicle components such as batteries, drive-train, and thermal management devices. Collaborate with cross-functional teams to identify edge cases and hardware-software corner cases that impact vehicle safety and performance. We’re excited about you because… BS/MS degree in Computer Science, Robotics, Electrical Engineering, or related technical field. 5+ years of experience in validati

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

Overview: Qsight is a high-growth division of Guidepoint focused on building data intelligence solutions for the healthcare sector. Qsight leverages proprietary datasets and rigorous analysis of alternative data sources to generate actionable insights for top-tier institutional investors, medical device manufacturers, and pharmaceutical companies. The Qsight team develops market intelligence products designed to be highly relevant, accurate, and scalable – delivering superior insights to a diverse, global client base. We are seeking an experienced, motivated Tehnical Operations Engineer to join our growing team. This is a multiple-hats role focused on SaaS/platform operations and tier-2 support for client-facing systems. You will own the administration and reliability of key tools, troubleshoot and resolve escalations with clear documentation, and build lightweight automation and reporting to reduce manual work as we scale. You will partner closely with Customer Success, Product, and Engineering to proactively monitor, support, and improve critical systems. Through practical, creative problem-solving, you will strengthen reliability, accelerate time to resolution, and increase operational visibility. Day to day, you will triage and resolve client technical questions, manage vendor license administration and renewals, and produce reporting that informs operational decisions. This role is a launchpad toward an SRE/Platform Engineering track as you grow into deeper automation, reliability engineering, and systems design work. This is a hybrid position based out of our Toronto office. What You’ll Do: Platform Support Own routine ops and configuration changes for critical SaaS platforms – Including Tableau, Freshdesk, Datadog, and our own client facing and internal portals Configure and maintain Freshdesk portals, routing, SLAs, permissions, integrations, etc. based on business requirements. Automate manual operations with Python, PowerAutomate, and shell scri

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 solid, experienced Software Engineer to join our Stations Software Platform team to work on helping us transition our customers to our latest generation platform and to make the platform evolve in a solution that can be brought to multiple different markets and business models. Technical interviews and interactions with the other offices in the company will be in English; however, the working environment in Montreal is bilingual. Responsibilities: Help define the roadmap and architecture based on technology and business needs Write well-crafted, well-tested, readable, maintainable code Have a good grasp and ability to explain the various tradeoffs made in decisions Participate in code reviews to ensure code quality and distribute knowledge Lead projects from idea to positive execution Incorporate considerations for business context and failure modes in your work Proactively participate in resolving ongoing incidents Unblock, support, effectively communicate and obtain buy-in across teams to achieve results Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices Experience: BSc/MSc in Computer Engineering, Computer Science, related field or relevant work experience 5+ years of software engineering industry experience Experience with object-oriented programming Experience in distributed systems Experience with Java and/or Python, familiarity with Scala is a plus Experience working with databases, relational or NoSQL Experience writing clear, scalable and clear design documentation Experience designing, building and improving a set of team owned components Must have a track record of professional excellence Benefits: Extend

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 Trust & Safety function at Lyft is dedicated to keeping every Lyft ride safe for both riders and drivers. We build and maintain the tools, features, and systems that deter bad actors, protect vulnerable populations, and reinforce trust across the platform. As an Backend Engineer working on Trust & Safety, you'll work at the intersection of product, design, engineering, and policy to ship high-impact safety features to millions of users. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience. Work closely with cross-functional teams and partner teams to develop solutions based on technology and business needs, and advance team’s goals and priorities Independently lead features from idea to positive execution and launch Unblock, support and communicate with internal partners to achieve results Write well-crafted, well-tested, readable, maintainable code Utilize your expertise in Python, Golang, AWS to deliver robust and scalable solutions Participate in code reviews to ensure code quality and distribute knowledge, as well as on call rotations Share your knowledge by giving brown bags, tech talks, and promoting appropriate tech and engineering best practices Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or related field or relevant work experience 3+ years of software engineering industry experience Extensive experience in object oriented programming, ideally in GoLang or Python Experience in backend software development of distributed systems and concurrency Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family bui

Mission Systems Engineers (Associate or Experienced) Company: The Boeing Company Boeing Defense Space & Security (BDS) has an exciting opportunity for Mission Systems Engineers (Associate or Experienced) to join our Experimental Systems Group (ESG) located in Seal Beach, CA; with options to work from Aurora, CO or El Segundo, CA ; to support development of new first-of-kind space vehicles and missions. ESG supports a variety of government customers spanning technology domains, and is an extremely fast-paced, responsive development environment delivering new capabilities to customers rapidly and affordably. The ESG portfolio consists of a range of platforms and technologies including the X-37B, the world’s first fully autonomous reusable spaceplane, which is continuing to shape the future of space technology while flying its eighth mission. As a mission systems engineer, you will be expected to lead modelling and simulation efforts and enable your assigned programs’ development from early capabilities studies through demonstration. You will serve as a core point of contact for customers and will work directly with subject matter experts across the business to quickly iterate and converge on achievable solutions that meet our customers’ needs. Our development timelines are aggressive, and you will be asked to develop solutions to previously unsolved problems. In this role, you will work in multidisciplinary teams to bring concept of operations to fruition in support of our customers’ mission objectives. You will work both as an individual contributor and as a product lead. An ideal candidate has a strong technical background across all spacecraft subsystems with particular depth in Attitude Control Systems (ACS)/Guidance Navigat

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 Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

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 Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

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 is seeking an Analyst to join our Business Forecast & Planning team within Customer Care Operations. This role owns the forecasting, capacity, and scheduling models that keep our global support workforce sized and staffed correctly. You'll work hands-on with our BPO partners to translate demand signals into staffing plans, and bring deep contact centre planning expertise to a team managing support at scale across multiple sites and geographies. Responsibilities: Support the development and upkeep of the models and frameworks that connect business drivers to staffing and resourcing decisions Translate large, complex, and sometimes ambiguous data into clear, actionable insights that support leadership recommendations Own day-to-day planning execution, from dashboards maintenance and reporting to business reviews, with a sharp focus on accuracy and the details that matter Leverage AI tools to build and maintain dashboards, reports, and analyses that support the team's recommendations and insights Identify and help drive opportunities to improve how the team plans and operates Move quickly on ambiguous, time-sensitive requests, using modern tools to work smarter and faster Experience: 2+ years in planning, forecasting, capacity/resource management, or a related analytical role; consulting, investment banking, FP&A, or ops strategy backgrounds also fit well Sharp analytical mindset with hands-on SQL and Python skills AI fluency, comfortable using AI tools to accelerate analysis and problem-solving Strong business acumen paired with genuine curiosity about how large, complex business systems work; fast learner with a bias towards action, comfortable building context quickly across new systems and stakeholders Self-directed, with a track record of turning data into real decisions; strong commun

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 Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. Agentic AI is at the center of how we scale that mission. We fine-tune and align open-source models, build AI-powered support agents, and develop end-to-end AI agents for safety case management, systems that reason over complex, high-stakes cases and drive them to resolution. SCC brings together ML, data, backend, and product engineers alongside data scientists and operations partners to transform these systems. As a Machine Learning Engineer on the SCC team, you will fine-tune and align models and build AI Agents that power how riders and drivers get help. Your work spans the full loop: post-training open-source models for our domain, composing them into multi-step agents, and building the evaluation that proves they are safe to ship in a customer-facing, safety-critical setting. Post-train and adapt open-source LLMs for SCC use cases using SFT, LoRA, and preference-tuning methods (RLHF, RLAIF, RLVR). Design and build AI-powered support agents and end-to-end agents for safety case management using LangGraph or equivalent agentic frameworks. Own the evaluation data flywheel, offline and online, that defines what "good" looks like and build benchmarks for the team to hill-climb. Turn interaction feedback into training data and learning signals, closing the data flywheel that continuously improves the models. Responsibilities: Conduct literature review and build post-training fra

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 Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe

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 a Data Scientist in the Pay, Integrity & Identity org, you will collaborate with our world class team of engineers, product managers, analysts and other data scientists to help create best in class pay platforms, stop fraudulent actors from harming our riders & drivers fraud and build user trust on the Lyft platform. You will run experiments (A/B tests) and develop data driven solutions to launch new features and remove the bad actors from the Lyft platform while maintaining a positive experience for genuine users. We’re looking for an intellectually curious individual who has extraordinary attention to detail, a track record of analytical problem-solving and skilled communication. Prior experience in the fintech, fraud or identity space is preferred. Responsibilities: Design and analyze experiments in collaboration with other scientists, product & engineering; communicate findings to stakeholders and facilitate launch decisions Leverage advanced statistical techniques to generate quantitative insights and develop machine learning models Analyze the wide variety of signals available to identify patterns in large datasets and uncover root causes Partner with product managers, engineers, and operators to translate analytical insights into decisions and action Build data pipelines and develop analytical frameworks to monitor business and product performance Set business metrics that measure the health of our products, as well as passenger and driver experience Collaborate with product and engineering and 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 relevant work experience 4-6+ years of industry experi

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

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 is seeking a Senior Analyst to join our Business Forecast & Planning team within Customer Care Operations. This role sits at the center of forecasting and capacity strategy for our global support organization, translating complex operational and business signals into clear, actionable plans. You'll partner closely with operations leadership to keep resourcing aligned with the business, separating what truly matters from the noise, and helping shape decisions that affect how we staff and scale support. Responsibilities: Support the development and upkeep of the models and frameworks that connect business drivers to staffing and resourcing decisions Translate large, complex, and sometimes ambiguous data into clear, actionable insights that support leadership recommendations Own day-to-day planning execution, from dashboards maintenance and reporting to business reviews, with a sharp focus on accuracy and the details that matter Leverage AI tools to build and maintain dashboards, reports, and analyses that support the team's recommendations and insights Identify and help drive opportunities to improve how the team plans and operates Move quickly on ambiguous, time-sensitive requests, using modern tools to work smarter and faster Experience: 2+ years in planning, forecasting, capacity/resource management, or a related analytical role; consulting, investment banking, FP&A, or ops strategy backgrounds also fit well Sharp analytical mindset with hands-on SQL and Python skills AI fluency, comfortable using AI tools to accelerate analysis and problem-solving Strong business acumen paired with genuine curiosity about how large, complex business systems work; fast learner with a bias towards action, comfortable building context quickly across new systems and stakeholders Self-directed, with a track

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 Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges—from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. We are looking for an experienced and highly motivated Data Scientist to join the Central Market Management team and lead key initiatives that enhance the quality of our overall decision-making. You’ll work cross functionally with other Data Scientists, Data Analysts, Product Managers, and Finance partners to make sure we are making the most financially efficient decisions to scale our business. You will identify gaps in our operational processes and measurements, and work to create strategies, frameworks, and models to help address them and deliver impact. Responsibilities Leverage data and analytical frameworks to identify opportunities for improving operational efficiency Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope Define and implement a robust attribution framework to evaluate the performance of high-stakes decisions Act as a technical lead, guiding other Data Scientists and fostering a culture of analytical excellence Write efficient, clean, production-level code (Python, SQL), ensuring reproducibility, documentation, and long-term maintainability of analytical assets B