Staff Business Systems Analyst in Canada

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. 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

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. Join the engineering team that builds the AI-native apps, agents, and tools the rest of Amplitude runs on. We are full stack, automation, integration, and data engineers delivering internal apps, data products, automations, and integrations to Finance, People Ops, Product Ops, Legal, HR, and more. We embed in each team, become experts in their business problems, partner on the solution, and accelerate time-to-value. This is an AI-first, full-stack software engineering role spanning the complete scope of our team’s work. Your engineering experience and fluency with frontier AI technologies will drive continuous improvements in both the systems we build the way we build them. The sum total of this work will produce meaningful business impact on the way all of Amplitude’s critical business functions operate. As a Senior Software Engineer, you will: Desi

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 fi nancial reporting. Team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Sta ff Software Engineer,Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs. You’re excited about this opportunity because you will... Own critical data systems that support multiple products/teams Develop, implement and enforce best practices for data infrastructure and automation Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services 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... 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects 6+ years experience working in data platform and data engineering or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Pro fi ciency in programming languages such as Python/Kotlin/Scala 4+ years of experience in ETL orchestration and work fl ow management tools like Air fl ow Expert in database fundamentals, SQL, data reliability practices and distributed computing 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kaa/Flink/Spark Streaming Excellent communication skills and experience working

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? As a Senior Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality. You will work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

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! About the Role Cohere builds frontier AI for the enterprise. We're hiring a Senior Director of Integrated Marketing to bring our demand engine, product marketing, and field/partner motion under one strategic roof. This is the senior marketing leader most accountable for pipeline. You're the person who turns Cohere's product, brand, and category narrative into qualified enterprise opportunities for our sales team. Sub-functions report to you: Product Marketing, Web Marketing, Growth, and Events & Partnerships. You'll work with the Chief of Staff on planning, budget, and operating cadence, and with the Marketing Operations Director and her analytics team on attribution, forecasting, martech, and the dashboards your pipeline number lives in. The demand engine only runs if you and the analytics group work as one team on measurement, and building that partnership is part of the job from week one. This role is built for someone who has done it before at a high-growth B2B SaaS or infrastructure company, and is ready to do it again at the frontier of AI. What You'll Run Integrated marketing strategy Build and run the integrated mark

About the Team DoorDash Labs, established in 2018, serves as the innovation hub for DoorDash, focusing on developing automation and robotics solutions to enhance last-mile logistics. The team's mission is to create technologies that support and augment human networks, aiming to improve efficiency for Dashers, merchants, and consumers alike. We’re ruthlessly focused on business impact. We are a highly senior team composed of former pioneers from a variety of different robotics industries. As of 2025, DoorDash has completed 10B lifetime deliveries. We’re focused on how to do the next 10B even better. About the Role We are seeking a highly motivated Senior/Staff Test Engineer to join our team. This individual will play a key role in the development and validation of our unmanned platforms at the system and component levels. The ideal candidate has a strong background in test development, test execution, and root cause analysis with a proven track record of collaboratively managing risk throughout a fast paced development process. You’re excited about this opportunity because you will… Run and monitor tests within our facility as well as at outside test labs. Collaborate with a tight knit team to identify and understand test failures. Be hands-on in developing test methods and equipment to uncover failures before they happen in the field. Find clarity through root cause analysis of lab and field failures and suggest design changes to prevent them. Use your creativity to create novel and scaled tests for autonomous systems. We’re excited about you because you have… A bachelors or advanced degree in a relevant engineering discipline. Mastery of test equipment such as environmental chambers, vibration tables, water testers, DAQs, etc.. Ability to bring order to complex test and development programs via clear technical communication and documentation. Experience designing and building testers and equipment. Ability to write Python scripts to automate

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 looking for an Engineering Manager from across multiple disciplines. We are growing our team with people who want to build, improve, and incorporate technologies that make the lives of our community more enriched. As an Engineering Manager at Lyft, you'll collaborate with other teams and orgs, product managers, designers, data scientists, analysts, and operations on technology that empowers us to iterate quickly, while focusing on delighting our passengers and drivers. The Rider organization is focused on building a seamless, best-in-class rideshare experience for riders. From the foundational functionality of requesting a ride to the tailored interactions with specific verticals like your flight, we sweat the small stuff to help make Lyft the best transportation solution. As an Engineering Manager on the Rider vertical team, you will act as a critical technical leader, taking holistic ownership of supporting current projects and delivering new products from 0 to 1. This includes developing complex systems, defining strategic roadmaps, driving cross-functional alignment, and ensuring engineering excellence to improve the rideshare experience. Responsibilities: Drive team execution, proactively resolve bottlenecks and make decisive trade-offs. Partner with cross-functional teams (Product, Design, Marketing, Science, and Analytics) to define the team's strategic direction. Translate high-level business goals into actionable projects. Own a team roadmap from conception to delivery, managing cross-team dependencies and mitigating risks. Maintain operational excellence through contributing to best practices for observability, reliability, and on-call processes. Ensure technical excellence through architecture reviews, tech debt management, and engineering guidance. Maintain team health

You love turning real business problems into working AI solutions — and you’re not afraid to roll up your sleeves to ship them. In this role, you’ll lead Diligent’s internal AI Solutions function , a small, high-impact team that is embedding AI and GenA I into the systems thousands of colleagues use every day across Marketing, Sales, Customer Success, Finance, HR, Legal, and Product & Engineering. You’ll set the AI vision and roadmap for internal tools, architect solutions, and still build hands-on — from prototypes and reference implementations through to production-grade integrations . You’ll own how AI shows up inside ERP, CRM, BI and core IT platforms, and you’ll be accountable for making those solutions reliable, secure, compliant, and measurably valuable for the business. If you enjoy being a “player-coach” who can move seamlessly between executive conversations and deep technical reviews, this role gives you the scope, visibility, and impact to shape how a global SaaS leader uses AI to run smarter and faster. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead, coach, and grow a high-performing team of AI Solutions Architects and Engineers, setting clear goals and building the capabilities the business needs as AI demand scales. Define and own the strategy, vision, and roadmap for internal AI solutions, translating business priorities into a focused portfolio of AI and platform initiatives. Design and deliver end-to-end AI/GenAI solutions — from ideation and prototyping through production deployment, monitoring, and continuous improvement. Embed AI capabilities (such as RAG, copilots, agents, summarization, and classification) into core business applications including ERP, CRM, BI, and other enterprise systems in a robust, maintainable way. &nbsp

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About This Role We're looking for a Staff HR Business Partner to build and own the people strategy for Snorkel's Data as a Service (DaaS) organization. This role is hybrid ( 3 days/week in office) in San Francisco, CA . The DaaS org is a delivery-first team that has more than tripled in size over the last six months, with no signs of slowing. They deliver high-quality data operations and AI deployment outcomes for frontier labs and AI teams. This org has a unique composition: forward deployed engineers, technical and operations delivery managers, a supply team managing a workforce comprised of multiple worker types at scale, and others. The people challenges here require an HRBP who has seen this kind of complexity before, such as workforce planning across FTEs and contractors, building a high performance culture rooted in delivery outcomes, and keeping a geographically dispersed, operationally complex team connected to Snorkel's culture. You'll partner directly with our DaaS GM and leadership team, and you'll need to be as comfortable in the operational weeds as you are in strategic conversations. The ideal background is professional services, managed services

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 Lyft Business organization builds the platform that lets organizations move the people they depend on employees, clients, and customers. From the foundational mechanics of a company funding and provisioning a ride to the tailored workflows that get an employee to a client meeting or home after a late shift, we sweat the small stuff to make Lyft the transportation solution businesses build their programs on. As a Staff Software Engineer on the Lyft Business Team, you will act as a critical technical leader, taking holistic ownership of complex systems that span the rider experience, the administrator experience, and the enterprise integrations behind them — defining strategic roadmaps, driving cross-functional alignment, and driving engineering excellence to improve how organizations move their people. Responsibilities: Shape the long-term architecture for systems, taking accountability for both short-term functionality and long-term health Translate high-level business goals into actionable engineering projects. Own the technical roadmap from conception to delivery, managing cross-team dependencies and mitigating risks Champion improvements in system, observability, performance, and tech debt reduction, extending your influence beyond your immediate team Establish best practices for deployment, alerting, and on-call health. Take holistic ownership of the platform's stability, tracking down issues root causes and building preventive safeguards for your immediate scope and beyond. Drive alignment across product, design, and operations. Proactively resolve bottlenecks and make decisive trade-offs to protect system architecture from competing organizational priorities Mentor and level up the engineers around you. Delegate stretch opportunities, lead cross-team reviews, and foster a culture of s

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.

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! The Opportunity As a Staff Security Engineer, you will be a hands-on technical leader strengthening security across Forma's application, cloud infrastructure, development lifecycle, internal systems, and incident-response practices. Security today is shared across Engineering and DevOps. You'll work closely with both teams and have real room to shape how Forma approaches security as we grow. Depending on your interests and the needs of the business, the role could develop into a deeper individual-contributor position or help build a dedicated security team. You'll work directly with Engineering, DevOps, IT, Product, Legal, and Privacy to identify risks, design practical controls, automate security processes, and help teams ship secure and reliable software. What you'll do Cloud and infrastructure security Design and implement security controls across Forma's AWS environments, with a focus on IAM, least-privilege access, service identities, and account boundaries. Embed security requirements into Terraform and other Infrastructure as Code, and improve secrets, certificate, encryption-key, and credential management. Build automated checks for insecure configurations, excessive permissions, exposed resources, and configuration drift across Kubernetes, containers, serverless workloads, networking, and data services. Application, data, and AI security Run threat modelling and security architecture reviews for new products, services, APIs, data pipelines, and third-party integrations