Cost Estimation Manager in Toronto

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As a Software Engineer on the Acceleration Kernel Development team at Tenstorrent, you’ll work at the intersection of software and hardware performance. You’ll be writing low-level code that directly powers high-efficiency machine learning workloads, optimizing every cycle, every memory move, every instruction. If you're motivated by performance, precision, and real impact, this is where your skills will shine. This role is hybrid, based out of Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A developer who loves high performance code, parallel algorithms, wrangling bits, optimizing compute, and making hardware fly. Great in C/C++ and able to build fast, efficient code from the ground up. Obsessed with performance and precision, especially in ML workloads. Motivated by complex problems and thrives in collaborative, fast-moving environments. What We Need Expertise in building and optimizing compute kernels for parallel ML and high-performance workloads. Ability to analyze and tune instruction-level performance across latency, memory, and bandwidth. A collaborative mindset to work closely with ML engineers and integrate opti

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building next-generation CPU and AI silicon. You’ll work at the forefront of hardware innovation, diagnosing complex issues across chips, systems, firmware, and software while collaborating with some of the brightest engineers in the industry. This role offers the opportunity to solve challenging technical problems, build impactful debug solutions, and directly influence the reliability and performance of cutting-edge AI compute platforms. This role is hybrid, based out of Toronto, Canada. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Experienced in hardware debug and post-silicon bring-up for CPU, SoC, or ASIC systems. Strong understanding of processor architecture and microarchitecture (RISC-V, x86, or ARM) with familiarity in debug and trace methodologies (e.g., iJTAG). Hands-on engineer who excels at diagnosing complex hardware, firmware, and software issues through root-cause analysis. Comfortable working in the lab with a passion for building debug tools, automation, and scalable methodologies. Collaborative team player with experience partnering across ASIC, firmware, software, and validation teams. What We Need

Want to work in technology at an investment bank? Graduate training, ongoing support, opportunities at leading global employers – the Alumni graduate program gives you everything you need. (And don’t worry, there’s no training bond. No exit fees, no hidden catches). Here at mthree, we pair great graduates with brilliant global businesses. Our clients include tier one investment banks and other organizations across a range of industries, from insurance to healthcare to travel. mthree has an exclusive partnership with Columbia Univ. School of Engineering. All mthree Alumni are eligible to receive two Executive Education certificates from Columbia Engineering as part of their Academy and industry placement experience at no cost. Further, all participating Alumni will have access to the Columbia Engineering network and ongoing training. What you'll do: Production support plays a vital role in enterprise technology, from algorithmic trading engines to regulatory reporting. Think of it as healthcare for technology. As a production support analyst with mthree, you’ll be on a shared mission to look after the technical systems and processes other teams rely on. How the Alumni program works: Apply via this job advert. Complete our assessment process. Get trained at mthree Academy in an online class for 4-8 weeks with other graduates. Join a mthree client for 12-24 months while receiving support and salary increases every 12 months. The vast majority then convert to permanent employees with the client at the end of the program. What you’ll learn at the mthree Academy: How to discuss production support activity at a high level including ITIL (information technology infrastructure library), monitoring, DevOps, SRE (site reliability engineering), and disaster recovery. How to discuss common financial topics, including financial markets, equity trading, derivatives, currency, treasury, regulation, and risk. How to write a basic computer program in Python, including user input

Want to work in technology at an investment bank? Paid graduate training, ongoing support, opportunities at leading global employers – the Alumni graduate program gives you everything you need. (And don’t worry, there’s no training bond. No exit fees, no hidden catches). Here at mthree, we pair great graduates with brilliant global businesses. Our clients include tier one investment banks and other organizations across a range of industries, from insurance to healthcare to travel. mthree has an exclusive partnership with Columbia Univ. School of Engineering. All mthree Alumni are eligible to receive two Executive Education certificates from Columbia Engineering as part of their Academy and industry placement experience at no cost. Further, all participating Alumni will have access to the Columbia Engineering network and ongoing training. What you'll do: Production support plays a vital role in enterprise technology, from algorithmic trading engines to regulatory reporting. Think of it as healthcare for technology. As a production support analyst with mthree, you’ll be on a shared mission to look after the technical systems and processes other teams rely on. How the Alumni program works: Apply via this job advert. Complete our assessment process. Get trained at mthree Academy in an online class for 4-8 weeks with other graduates. Join a mthree client for 12-24 months while receiving support and salary increases every 12 months. The vast majority then convert to permanent employees with the client at the end of the program. What you’ll learn at the mthree Academy: How to discuss production support activity at a high level including ITIL (information technology infrastructure library), monitoring, DevOps, SRE (site reliability engineering), and disaster recovery. How to discuss common financial topics, including financial markets, equity trading, derivatives, currency, treasury, regulation, and risk. How to write a basic computer program in Python, including user

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 flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

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 looking for experienced backend software engineers to join our claims tech engineering team. Our vision is to tangibly reduce risk on the Lyft platform, and by extension reduce insurance cost. Our team is dedicated to centralizing the entire claims operation onto a unified risk platform. This consolidation of data, workflows, and communications aims to foster proactive measures, enhance efficiency, ensure consistency, and provide valuable insights. These efforts are designed to effectively reduce claims costs as Lyft's operations expand. Additionally, our team is responsible for maintaining robust relationships with our third-party insurance partners, guaranteeing timely, proactive, and precise sharing of claim data. Responsibilities: Write well-crafted, well-tested, readable, maintainable code Own feature from product spec to successful high quality development, deployment and maintenance Participate in code reviews to ensure code quality and distribute knowledge Respond to external questions and requests. Unblock, support and communicate with stakeholders to achieve results Experience: 3+ years of relevant professional experience Experience with object-oriented programming Experience in distributed systems Experience working with databases, relational or NoSQL Write clear, scalable and clear design documentation Design, build and improve a set of team owned components Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Child care and pet benefits Access to a Lyft funded Health Care Savings Account RRSP plan with company match to help save for your future In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows

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 a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

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

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

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a Director of Machine Learning Engineering and Infrastructure to lead a hybrid team bridging advanced ML engineering with world-class infrastructure design. In this role, you will own the strategic direction and execution for scaling our machine learning capabilities while ensuring our distributed systems and infrastructure can support innovation at massive scale. You will combine technical depth with leadership excellence to guide teams that deliver both foundational ML systems and high-performance distributed services. This is a hybrid role for our Toronto office. What You'll Do: Lead and manage high-performing teams across ML engineering and ML infrastructure, fostering a culture of innovation, collaboration, and growth. Define and execute the strategic roadmap for ML systems, including recommendation, personalization, and ads optimization. Oversee the design, development, and deployment of scalable ML pipelines: data ingestion, feature engineering, model training, evaluation, and serving. Architect distributed systems to support ML workloads at scale, ensuring reliability, observability, and operational excellence. Partner closely with Product, Engineering, and Content teams to align on business goals and deliver impactful ML-driven experiences. Support best practices in experimentation, evaluation, and ML system monitoring. Ensure cost efficiency, scalability, and performance in ML infrastructure investments. Your Background: 10+ years of industry experience spanning machine learning engineering and distributed systems. 3+ years of leadership and management experience, with a proven ability to build and lead strong t

Level Up Your Career with Zynga! At Zynga, we bring people together through the power of play. As a global leader in interactive entertainment and a proud label of Take-Two Interactive, our games have been downloaded over 6 billion times—connecting players in 175+ countries through fun, strategy, and a little friendly competition. From thrilling casino spins to epic strategy battles, mind-bending puzzles, and social word challenges, our diverse game portfolio has something for everyone. Fan-favorites and latest hits include FarmVille™, Words With Friends™, Zynga Poker™, Game of Thrones Slots Casino™, Wizard of Oz Slots™, Hit it Rich! Slots™, Wonka Slots™, Top Eleven™, Toon Blast™, Empires & Puzzles™, Merge Dragons!™, CSR Racing™, Harry Potter: Puzzles & Spells™, Match Factory™, and Color Block Jam™—plus many more! Founded in 2007 and headquartered in California, our teams span North America, Europe, and Asia, working together to craft unforgettable gaming experiences. Whether you're spinning, strategizing, matching, or competing, Zynga is where fun meets innovation—and where you can take your career to the next level. Join us and be part of the play! Position Overview: Come join our team at Zynga making an impact across all of the company’s games - Mobile Game Tech (MGT). Lead the FinOps team by setting technical direction, crafting and implementing backend services for our games. We’re looking for outstanding engineers with a passion for technology and the desire to work in a team with dynamic strengths. This unique position will challenge you to tackle situations across a broad set of technical stacks, to soak up internal business logic from all kinds of teams, and to drive cost efficiency improvements across the organization. This FinOps team expands beyond just AWS and GCP and investigates cost optimization and unit economics for a variety of technology vendors. What You'll Do: Lead all technical aspects of the FinOps team’s software development an

ROLE: SENIOR FINANCE MANAGER LOCATION: TORONTO The Role Salt XC is looking for a Senior Finance Manager to lead the day-to-day financial management of The Kitchen, a large-scale embedded agency partnership with a Fortune 500 client. This role will be the primary Finance partner and point of contact for The Kitchen. While Salt’s broader Finance team will continue to execute transaction processing, including payroll, accounts payable, accounts receivable and expense processing, this person will sit at the centre of the operation—ensuring projects are financially controlled, billings happen on time, revenue and costs are appropriately recognized, reporting is accurate, and stakeholders have clear and timely visibility into the financial health of the business. This is an ideal role for someone with strong project accounting and revenue accounting experience who is equally comfortable working with Finance teams, agency operators, producers and senior client stakeholders. Key Responsibilities Project & Financial Management • Own the financial oversight of approximately 100-150 client projects annually • Maintain accurate project financials, including budgets, committed costs, actual costs, billings and project-level profitability • Ensure production costs and employee expenses are accurately captured and allocated to the appropriate projects • Monitor project financial activity from initiation through final reconciliation and close • Identify financial discrepancies, aging items and project risks and proactively drive them to resolution • Maintain strong financial controls while supporting the speed and flexibility required in an agency environment • Identify areas for efficiency and cost reductions Revenue, Billing & PO Management • Own the financial workflow between project teams, both internal and external, to ensure projects are billed accurately and on tim

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

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 builders and sharp problem-solvers who are wired to deliver great outcomes. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. The DevX team’s mission is to build and operate the core developer infrastructure at Robinhood. Our team owns and scales the systems that thousands of engineers rely on daily, partnering with software developers across the company to make development fast, reliable, and cost-efficient! As a Staff Software Developer, you will act as a technical leader for our build and developer infrastructure, driving the strategy and execution of the systems thousands engineers depend on every day. Your work will span our build systems, CI pipelines, and remote development environments, ensuring engineers can code, test, and build with speed, safety, and reliability at scale. In this role, you will collaborate with teams across Robinhood to eliminate developer friction and raise the bar for engineering productivity. This is a high-visibility leadership opportunity to shape our developer ecosystem and set new standards of engineering efficiency! 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-performing teams. What you’ll do Architect the long-te