Data Center Ssd Performance Validation Engineer in Canada

We believe communication belongs to everyone. We exist to democratize phone service. TextNow is evolving the way the world connects, and that's because we're made up of people with curious minds who bring an optimistic yet critical lens into the work we do. We're the largest provider of free phone service in the nation. And we're just getting started. Join us in our mission to break down barriers to communication and free the flow of conversation for people everywhere. TextNow is looking for an experienced Data Developer with hands-on experience designing and developing data platforms. You will own the design, development, and maintenance of TextNow's data platform, enabling us to make effective data-informed decisions. You will be part of cross-functional efforts to build scalable and reliable frameworks that support allTextNow's business and data products. In this role, you can interact with different functional areas within the business and influence decision-making in a fast-growing mobile communications start-up. This role is about impact at scale. You’ll shape how TextNow builds and operates its systems in an AI-first environment where intelligent tooling is embedded into everyday engineering practice. Using AI is not optional, it’s expected. From design and architecture to implementation, testing, debugging, documentation, and operational analysis, you will actively leverage AI tools to increase velocity, improve code quality, and make better technical decisions. We provide a robust suite of AI-powered development tools and workflows to support you, and we expect you to continuously evolve how you use them to raise the bar for efficiency, clarity, and product excellence across the organization. What You'll Do Own TextNow's data warehouse, data pipelines, and integration points between various business systems. Design, develo

We believe communication belongs to everyone. We exist to democratize phone service. TextNow is evolving the way the world connects, and that's because we're made up of people with curious minds who bring an optimistic yet critical lens into the work we do. We're the largest provider of free phone service in the nation. And we're just getting started. Join us in our mission to break down barriers to communication and free the flow of conversation for people everywhere. TextNow is looking for an experienced Data Developer with hands-on experience designing and developing data platforms. You will own the design, development, and maintenance of TextNow's data platform, enabling us to make effective data-informed decisions. You will be part of cross-functional efforts to build scalable and reliable frameworks that support allTextNow's business and data products. In this role, you can interact with different functional areas within the business and influence decision-making in a fast-growing mobile communications start-up. This role is about impact at scale. You’ll shape how TextNow builds and operates its systems in an AI-first environment where intelligent tooling is embedded into everyday engineering practice. Using AI is not optional, it’s expected. From design and architecture to implementation, testing, debugging, documentation, and operational analysis, you will actively leverage AI tools to increase velocity, improve code quality, and make better technical decisions. We provide a robust suite of AI-powered development tools and workflows to support you, and we expect you to continuously evolve how you use them to raise the bar for efficiency, clarity, and product excellence across the organization. What You'll Do Own TextNow's data warehouse, data pipelines, and integration points between various business systems. Design, develo

About the job Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain.We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions. As Artefact continues to grow in the US, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption. Who We Are Founded and headquartered in Paris, Artefact is a next-generation consulting firm, specializing in data, analytics & AI consulting, dedicated to transforming data into business impact across the entire value chain of organizations. We are proud to say that we help our clients grow their data and digital capabilities, and that we’re also growing in parallel. We have 2000 employees across 36 offices who are focused on accelerating digital transformation. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts are all dedicated to bringing extra value to every client. We design data-based solutions to meet our clients' specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we've acquired with our 1000+ client base around the globe. Find out more at artefact.com . What you will be doing Artefact is looking for a Senior AI & Data Scientist: a scientist who owns models end to end, from problem framing thr

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. At Airtable, we're passionate about democratizing software creation — empowering anyone to build powerful, flexible tools without writing code. With our shift to an AI-native platform, customers can now generate full apps and deploy AI agents directly into their workflows. Data engineering plays a critical role in this evolution by delivering the insights our teams rely on to improve user experience, measure agent impact, and understand how the business is performing at scale. As a Software Engineer, Data at Airtable, you'll make an enormous contribution to our data engineering efforts. You'll design and own mission-critical data pipelines to enable decision-making, partner with company leaders to create scalable data solutions, and launch innovative alerting and visualization solutions. The Team Our team is embedded in how Airtable understands itself as a business, working closely with Data Science and Analytics. What's unusual here: the platform you're instrumenting is the same one your customers use every day. When Airtable ships a new AI agent capability, you're among the first to wire it up, measure its adoption, and influence what gets built next. Product & AI Data Infrastructure This team builds and owns the foundational data pipelines that power product analytics across Airtable. As Airtable shifts to an AI-native platform, our work increasingly involves instrumenting and measuring AI product usage, building event pipelines for AI agents, surfacing AI-native adoption metrics in core business tables, and developing AI-powered data discovery tooling, including vector search over our catalog metadata. We partner closely with product analytics, product engineering, and data infrastructure to turn business question

Join the team shaping the future of AI at Scale. Scale builds RL environments: sandboxed replicas of the digital spheres where real knowledge work occurs and built from the operating data of the companies that actually hold it. As the Data Acquisition Lead , you will own the commercial motion that gets us that data end to end. You will figure out which companies sit on the data for the next domain worth owning and then go and get it. This is a zero-to-one function with no playbook. You should be prepared to wear many hats, from thesis-driven dealmaker to hands-on operator to technical translator between commercial and Research teams. You will: Map the supply side. Work backwards from where labs are pushing to the specific organizations holding the underlying data. Build a thesis on which domains are worth owning and in what order. Invent the deal structures. You'll work with Scale’s legal team to define the first version of how these transactions get priced. Close. Own it from cold outreach to signature. Close the loop with the technical side. You need to hold a real conversation about what makes a dataset trainable and become an expert in what makes this underlying data valuable. Build the machine. Do the work by hand first, then turn what you learn into a repeatable pipeline. Ideally, you’d have: 5+ years across some mix of business development, corp dev, commercial strategy, or early-stage GTM. The label matters less than a track record of building a commercial motion that didn't exist before you got there A strong track record of managing important external relationships Strong business judgment and the ability to evaluate partnership value quickly Clear communication skills and comfort working with senior stakeholders Ability to operate independently while staying closely connected to cross-functional teams A practical, hands-on approach to building new functions from the ground up Comfort working in fast-moving, ambiguous environments Experience in

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

About the Team The Analytics team is looking for experienced Data Scientists and Senior Data Scientists to guide measurement, strategy, and tactical decision-making across the company across a variety of teams and levels. Data Scientists at DoorDash work to uncover insights and turn them into relevant recommendations, driving decisions for the entire organization. Analytics is integral to all operational areas at DoorDash. Please apply here for all non-managerial levels within the following analytics teams: Consumer & Growth Business Operations Dasher & Logistics Customer Experience & Integrity Merchant, Ads & Sales New Verticals International Data Science About the Role As a Data Scientist at DoorDash, you'll use your quantitative background to mentor other scientists and dive into large datasets to guide decision-making. We solve a multitude of exciting challenges including customer acquisition, fraud and support, marketing, balancing supply and demand, new city launches, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business Build full-cycle analytics experiments, reports, and dashboards using SQL, R, Python, or other scripting and statistical tools Work with and mentor junior analysts on how to use more advanced methods and solve challenges Produce recommendations and use statistical techniques and hypothesis testing to validate your findings Provide insights to help business and product leaders understand marketplace dynamics, user behaviors, and long-term trends Identify and measure levers to help move essential metrics and make recommendations Work backwards from understanding and sizing problems to ideating solutions Report aga

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

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

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

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. Interns work side-by-side with top engineers in the industry while having autonomy from the get-go. They contribute to user-facing products and are able to see their work go live quickly. Lyft fosters a collaborative environment in the office, so there's always a sharp mind eager to hear about your next idea. So what's yours? Responsibilities: Own your project, while checking in with other team members throughout the day with questions and updates You leave the code in a better state than when you found it (progressive refactor) You value reliability, ensured by testing Participate in code reviews to ensure code quality and distribute knowledge Continuous integration and deployment Go home knowing that your work today is meaningfully improving the lives of every Lyft driver and every Lyft passenger! Experience: Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science or related major 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 an internship in Toronto Strong knowledge of CS fundamentals Knowledge of SQL and data modeling fundamentals Experience working with databases Excellent communication skills Interest in solving large scale data problems in a real world scenario Passion for community, sustainability, and/or transportation Benefits: Mental health benefits In addition to holidays, interns receive 2 days paid time off and 3 days sick time off Subsidized commuter benefits and Lyft ride credits Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft belie

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 on the Mapping team, you will collaborate with our world class team of scientists, engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our geospatial, behavioural and mobility data, and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. The Mapping team serves models and systems that determine the most efficient routes, fastest travel estimates and process real-time map data signals to detect traffic, closures and slowdowns. Working with our business and analytics partners, the team owns tools to ensure Lyft offers routes that our users trust. This will involve identifying and scoping opportunities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in Mapping, including: How do we accurately predict acute and chronic traffic conditions? How do we improve the recommendations of our routing algorithms? How do we keep our travel estimation promises to our riders and drivers? How do we benchmark and measure the success of our services? Responsibilities: Own the complete lifecycle of algorithmic solutions from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration Prioritize and lead deep dives into our data to uncover new product and business opportunities Partner closely with E

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. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, shaping team priorities, recommending and implementing technical solutions, designing experiments, and measuring the impact of new features. The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As a Data Scientist on the Airport team, you will collaborate with our team of engineers, product managers, and designers to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product changes, develop end-to-end technical solutions, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: What rider segments are present at airports and how can we address their major pain points to grow our airport marketshare? What new airport product features can we introduce to grow rider demand? Are we able to forecast rider demand and use this prediction to adjust ride offerings or improve the rider experience? How can we optimize ride offerings for each rider to maximize conversion? Responsibilities Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Desi