Software Engineer Distributed Systems in Canada

Location: San Francisco, CA (Remote/Hybrid Available) What is Verse? The race to AI has become the race to power. Every breakthrough in artificial intelligence depends on one thing: access to electricity. But across the country, aging grid infrastructure and years-long interconnection queues are slowing the deployment of the data centers that will power the next generation of innovation. Solving this challenge isn't just about energy—it's about unlocking the future of AI. At Verse, we're building the energy intelligence platform for the AI economy. Our software helps the world's largest energy consumers achieve faster, cheaper, and cleaner power by combining real-time control of energy assets with complete visibility into their energy portfolio. Backed by Bessemer Venture Partners, GV, Coatue, and NVIDIA, and built by pioneers in grid-scale batteries, energy markets, and enterprise software, we're redefining how the world's most ambitious organizations access and manage energy. The Role As a Software Engineer focusing on Distributed Systems at Verse, you will work in collaboration with some of the brightest industry experts in the field building cloud-native applications that scale to trillions of data points collected from electricity markets globally. You will be a part of a dynamic, robust team primarily supporting the backend needs of our Aria software product spanning hundreds of data sources, sinks, services, and jobs. Your expertise will not only have a direct impact on product decisions, but you also be well-positioned to drive the development and trajectory of our entire platform and infrastructure and influence important architectural decisions that affect the whole organization. Key Responsibilities Foster a culture and mindset of well-designed systems, test-driven software, and transparent communication with a high caliber of mutual respect and consideration for stakeholders Read and write a lot of Go, Python, and Protobuf Build, test, debug, maint

About the Role: As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi. A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine. You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams. Responsibilities: Design and build scalable, high throughput, and low latency distributed systems using Scala Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art. Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc. Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi. Your Background: Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM b

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

About the Role: Tubi's content platform is the engine behind one of the largest free streaming services in the world. Every play, every deal, every creator, every frame of video flows through systems CPE owns, and the surface area is enormous. Distributed services running on the hottest path of Tubi's traffic. Video pipelines processing one of the largest workloads in streaming. Workflow engines automating the operations that used to consume entire teams. Creator-facing products turning a back-office process into a real platform. And on top of all of it, an AI-native rebuild of the CMS that most companies aren't willing to attempt. This isn't a single-domain role. It's a platform where backend, frontend, video, infrastructure, and applied AI all collide at the scale where decisions actually matter, where an architectural choice ripples across millions of titles and billions of requests, and where the difference between "good enough" and "great" shows up in revenue. We're looking for builders who want to range across domains — backend one quarter, frontend the next, applied AI the one after that — and who want their work to be felt: by viewers when a title plays instantly, by creators when they go live the same day, by Content Ops when a workflow runs itself, and by the business when the platform stops being a cost center and starts being a force multiplier. The infrastructure is already there. The mandate is already there. What's missing is the people who want to build the thing, not talk about it. Come build it. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: You'll work on systems that sit at the heart of Tubi's business, where the content pipeline meets the viewer, the creator, and increasingly, the AI agent. The work spans the full stack of a modern content platform: distributed services, video infrastructure, workflow automation, and applied AI, all running at

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas

About the Team The Storage teams build and operate online stateful systems and abstractions that are reliable, efficient, secure and easy to use for DoorDash Engineering. The teams are responsible for understanding Product Engineering’s evolving needs and developing platform and infrastructure capabilities to serve them. The team currently supports CockroachDB, Cassandra, Kafka and Redis as well as data abstraction services to reduce the complexity of interacting with storage systems for Product Engineers. About the Role The Storage team is building and operating a high-performance, scalable, and reliable data abstraction layer that optimizes both efficiency and reliability. Our goal is to create a platform that manages itself and fades into the background—empowering engineers to focus on delivering product experiences our customers love. This role is available across two teams within Storage, each solving unique and high-impact challenges: One team is building the orchestration layer for DoorDash’s storage platform—unifying lifecycle management, operations, and self-serve APIs for databases and streaming systems, turning complex, stateful infrastructure into reliable, developer-friendly services used across the company. One team builds and operates the distributed data platform powering DoorDash's largest stateful workloads -- including Cassandra, which backs critical product surfaces across DoorDash, Wolt, and Roo. You'll design high-throughput data abstractions, smart clients, and platform services that make distributed data reliable and easy to work with at multi-petabyte, multi-million-QPS scale, with opportunities to go deep on distributed systems internals and contribute to the open-source Cassandra ecosystem. If you're passionate about distributed systems, developer experience, and building foundational infrastructure at scale, we'd love to hear from you. You must be located in San Francisco, Sunnyvale, Seattle, or the New York Metro Area for this hybrid pos

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. Marketplace teams are at the heart of our products and decision-making, owning everything from rider pricing to driver earnings, incentives, and efficient matching. We’re looking for passionate, driven engineers to build systems that empower our riders and drivers to have the best transportation experience possible through prediction, adaptivity, and personalization. We’re looking for someone who is excited about working in a fast-paced, innovative, and impactful environment to create reliable solutions to distributed computing, ML, and data problems. The Pricing team is a centerpiece of Lyft’s Marketplace org, determining prices for all rideshare products and supporting new initiatives. Rider Engagement develops rider-facing engagement levers and optimizes user pricing experience to drive both short term and long term business outcomes. We work with Product & Science to solve and implement complex pricing requirements, balancing the needs of riders, drivers, and the business goals. As an owner of one of the most critical flows in the company, you will work on a wide array of challenges such as latency-sensitive concurrency problems, large scale distributed systems, and experimentation. If you’re interested in playing a large part in demand / supply management and improving the Lyft customer experience, this could be a great fit for you. 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, maintaina

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. Marketplace teams are at the heart of our products and decision-making, owning everything from rider pricing to driver earnings, incentives, and efficient matching. We’re looking for passionate, driven engineers to build systems that empower our riders and drivers to have the best transportation experience possible through prediction, adaptivity, and personalization. We’re looking for someone who is excited about working in a fast-paced, innovative, and impactful environment to create reliable solutions to distributed computing, ML, and data problems. The Pricing team is a centerpiece of Lyft’s Marketplace org, determining prices for all rideshare products and supporting new initiatives. Rider Engagement develops rider-facing engagement levers and optimizes user pricing experience to drive both short term and long term business outcomes. We work with Product & Science to solve and implement complex pricing requirements, balancing the needs of riders, drivers, and the business goals. As an owner of one of the most critical flows in the company, you will work on a wide array of challenges such as latency-sensitive concurrency problems, large scale distributed systems, and experimentation. If you’re interested in playing a large part in demand / supply management and improving the Lyft customer experience, this could be a great fit for you. 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, maintaina

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 an Observability team member, you are responsible for the operation and maintenance of our logging and metrics infrastructure. You ensure all teams at Lyft are aware of the operational health of their products by monitoring system availability and take a holistic view of our platform performance. You build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you find opportunities to improve our systems in order to push our platform forward. You provide our partners with the support they need to help them build robust large scale distributed systems. We count on the reliability of our infrastructure to empower Lyft teams to provide our customers rich experiences that are highly available with rock solid performance to ensure our transportation platform continues to connect people and places. As we grow our team, we are seeking experienced Infrastructure Engineer to ensure that as our Infrastructure continues to scale, our platform continues to provide an essential and dependable service that transports millions of people every day. Specifically we are searching for someone who brings fresh perspectives, enjoys collaborating with cross-functional teams in order to continually improve our products and services for our customers. Responsibilities: Maintain, improve, and develop tooling and systems that enhance the reliability, scalability, and efficiency of our platform. Assist engineering teams in defining service-level objectives (SLOs) and provide the necessary toolin

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

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 are building and maintaining a highly scalable asynchronous platform that empowers our organization to handle critical business cases. As a software engineering team, our mission is to create robust and innovative solutions that drive the success of our business and deliver unparalleled value to our customers. We adopt Infrastructure as Code practice to automate the provisioning and configuration of our resources, which helps reduce manual configuration and improve consistency. Our team culture is built on collaboration, open communication, and a supportive environment where each member's ideas are valued and contributions are recognized. We believe in the importance of fostering a positive workplace culture that inspires innovation and creativity. 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 production readiness reviews, platform management and capacity planning ceremonies with cross-functional teams Document Infrastructure operations process and insights, identify repeatable actions and ruthlessly automate repetitive tasks Participate in our teams on-call rotations, respond to incidents and support other teams mitigate customer impacting events Experience: 5+ years experience working on teams responsible for software development, automation and systems engineering Experience building large-scale infrastructure, distributed systems or networks. Knowledge with SQS,

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. With over half a billion rides and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. Building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives requires robust, scalable software systems operating at massive scale. Our highly motivated Software Engineers work on these challenging problems and build the systems that directly impact various aspects of our core business. If you are a critical thinker with experience building software systems, passionate about solving business problems through well-crafted code and working in a dynamic, creative, and collaborative environment, we are searching for you. As an associate software engineer, you will be designing, building, and launching the services that power the platform's core products. Compared to similarly-sized technology companies, the set of problems that we tackle is incredibly diverse. They cut across transportation, distributed systems, backend services, mapping, personalization, and real-time infrastructure. We are hiring motivated engineers across each of these areas. We're looking for someone who is passionate about solving problems with code, building reliable and maintainable systems, and is excited about working in a fast-paced, innovative, and collegial environment. You will report to a Software Engineering Manager. Responsibilities: Partner with Engineers, Data Scientists, Product Managers, and Business Partners to build software for business and user impact Perform technical analysis and build proof-of-concept prototypes to explore and propose solutions to both new and existing problems Design and develop software components, services, and APIs Write production quality code to launc

Senior Software Engineer - Observability and Reliability About the Role We are growing the engineering team and looking for engineers who have the chops to build and deliver world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible. What You Will Be Doing Build observability tools and platforms, including: metrics, logging, distributed tracing, dashboarding, alerting, application performance management Build with modern tools and languages like Go, Open Telemetry and Kubernetes Participate in on-call rotation and ensure uptime of services Create runtime tools/processes that optimize cloud triaging and limit downtime Define best practices around making our systems and services measurable Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies. We expect successful candidates to be coding a majority of their time Qualifications We Need Strong Computer Science fundamentals 5+ years industry experience building and maintaining high-quality software, especially software other engineers use You apply a product mindset to infrastructure systems and feel accomplished enabling others Desire to be a great teammate and have fun at work Strong sense of craftsmanship, and a healthy academic curiosity Qualifications We Want (also, skills you’ll learn!) Experience building systems for data analytics Distributed systems monitoring and profiling skills Knowledge of cloud application security models Administered cloud service infrastructure (GCP, AWS, Azure) Startup experience Additional Job details Additional Job details The base salary range for this position is $170k - $240k annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize e

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 7+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries fo