Data Center Ssd Performance Validation Engineer 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. 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

Who are we? Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. 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. We like to work hard and move fast to do what’s best for our customers. Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products. Join us on our mission and shape the future! Why this role? We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models to be exact) learn in similar ways to humans - by way of feedback. By labelling, ranking, auditing, and correcting text output, you will improve Large Language Model’s performance for iterations to come, thus having a lasting impact on Cohere’s tech. Cohere seeks dynamic and dedicated Data Annotators with exceptional Modern Standard German Writing, Translation, and Data Manipulation skill. Please Note: This is a part-time independent contractor position available within Canada . We seek candidates who are able to commit to 16 hours per week minimum at a 30 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 months contract. Performance incentives included! As a Data Annotation Specialist, you will: Label and Rank: Accurately label and rank machine learning data with advanced proficiency in German, ensuring data integrity and quality. Audit and Correct: Sc

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? We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models, to be exact) learn in similar ways to humans, by way of feedback. By labelling, ranking, auditing, and correcting model output, you will improve Large Language Models' performance for iterations to come, thus having a lasting impact on Cohere's technology. We are hiring Generalist professionals with broad backgrounds that span multiple consumer-facing or personal domains. This is a judgment-driven role, not passive data entry. You will review, assess, and provide structured feedback across a broad and evolving range of tasks, evaluating, stress-testing, and improving our models on English-language data spanning multiple modalities (text, image, and structured formats such as JSON, CSV/TSV, and Markdown). This is a great opportunity for professionals with strong analytical skills to contribute to high-impact annotation projects. Please Note: This is a part-time independent contractor position available within Canada only. We seek ca

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? This role will focus on breaking down engineering tasks such as reporting, component search and handling of material billing/information into individual steps that can be tackled through tool use. Your breakdown will teach the Cohere model the logic needed to complete each task. Please Note: This is a part-time independent contractor position available within Canada . We seek candidates who are able to commit to 16 hours per week minimum at a 30 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract. Performance incentives included! As a Data Annotation Specialist, you will: Evaluate the model's ability to respond to engineering procedures and workflows Task models to complete engineering tasks along with verified information to evaluate the accuracy of the model's responses Label, proofread, and improve machine-written and human-written engineering-related outputs. Follow our style guide, and make recommendations on unique situations that fall outside of its scope. You may be a good fit if you have: 3+ years of industry experience working in eng

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? This role will focus on evaluating data science and coding tasks, requiring you to review and debug code, analyze model trajectories, and assess data visualization script development and logical flow implementation. Your work will contribute to our model development efforts and the logic our models apply when completing task requests. Please note : This is a part-time independent contractor position available within Canada. We seek candidates who are able to commit to 16 hours per week minimum at a 40 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract. Performance incentives included! As a Data Annotation Specialist, you will: Evaluate the model's ability to respond to coding requests, workflows, and code base-related questions using available tools. Assess agent trajectories and model capabilities for code generation, tabular and graphic manipulation, and debugging requests. Prompt models to complete complex data science tasks and review the accuracy of generated responses. Label, proofread, and improve machine-written and human-written soft

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? This role will focus on evaluating coding tasks, requiring you to review and debug code, navigate repository architecture, and analyze model trajectories. Your work will contribute to our model development efforts and the logic our models apply when completing task requests. Please note : This is a part-time independent contractor position available within Canada. We seek candidates who are able to commit to 16 hours per week minimum at a 40 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract. Performance incentives included! As a Data Annotation Specialist, you will: Evaluate the model's ability to respond to coding requests, workflows, and code base-related questions using available tools. Assess agent trajectories and model capabilities for code generation and debugging requests. Prompt models to complete complex coding tasks and review the accuracy of generated responses. Label, proofread, and improve machine-written and human-written software engineering-related outputs. Report quality and performance trends related to model/agent behavio

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

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Scientist working on Causal Inference in SCC, you'll partner with a strong team of engineers, product managers, designers, and operations leaders to deliver a personalized and exceptional experience for Lyft customers, using rigorous causal inference to guide the highest-stakes decisions we make. We're looking for a motivated and talented Data Scientist with deep causal inference expertise to join the SCC Data Science team. You'll partner closely with the area's tech lead on high-impact work spanning AI-powered support products, differentiated service, and operations optimization. The ideal candidate brings sharp applied inference intuition, a bias toward impact, and the ability to cut through ambiguity in complex problem spaces. You'll work on projects like: Design rigorous experiments and quasi-experiments to measure the causal impact of SCC product and AI-agent launches, and drive data-informed launch decisions. Build causal ML models to optimize concession budget allocation, targeting the right support credit, to the right rider or driver, at the right moment to maximize trust and business impact. Quantify the long-term effects of support-experience changes on rider and driver retention, and uncover heterogeneous treatment effects across our community. Deliver strategic insights on quality–cost tradeoffs, empowering leadership to balance service quality, coverage,

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

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 Driver Earnings team at Lyft is responsible for managing our suite of driver earnings products, driving top business goals around financial metrics and marketplace performance. The team develops and improves automation & execution of driver earnings products, develops new earnings products, and manages financial performance of these products to manage the growth of the business. We are looking for an analyst to join the team that is responsible for working with cross-functional stakeholders to analyze and improve existing earnings products and manage the products’ financial outcomes within the broader Marketplace organization. You will influence existing and future strategy with your data analysis, insights, and storytelling to deliver strategic recommendations on experimentation and product improvements. We’re looking for a data & process-driven individual who has extraordinary attention to detail and a track record of analytical problem-solving. Responsibilities: Support marketplace operations to provide world-class analysis, product recommendations, and reporting to stakeholders. Become an expert in marketplace trends and support weekly reporting structures for the Rideshare organization. Develop domain-specific subject matter expertise in our lever portfolio and support cross-functional initiatives to improve existing products and develop new ones. Analyze marketplace product & financial levers and provide cross-functional teams with actionable insights on improvements and problem areas. Operate within Rideshare decision-making frameworks with a critical lens, evaluating areas of improvement and business growth opportunities. Prepare regular business reviews for leadership, highlighting key areas of focus. Work with stakeholders and other teams to track, report, and r

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 is at the heart of Lyft Business's products and decision-making. We're looking to hire a Data Analyst to build the tools and analytics that drive revenue for the sales organization behind Lyft's B2B portfolio — a multi-billion-dollar book of business spanning healthcare, business travel, corporate commute, automotive, and transit. This team has real say in what gets built. You will be the analytical partner to our Sales and account teams — someone who can translate findings into a clear narrative for both technical and non-technical audiences. Responsibilities: Build the tools and analytics sales leaders use to grow their accounts — pacing views, account-health signals, territory and segment views that change what a rep or manager does next Field requests from Sales, Product, Finance, Legal, leadership, and external stakeholders, and decide what's worth building, what's worth a sharp piece of analysis, and what's out of scope Build and maintain production data pipelines, and automate recurring workflows, with documentation and validation clear enough that a teammate — or an AI agent — can use them without asking you first Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question Contribute to the internal tools and semantic layer — prompts, context, and guardrails — that let stakeholders query B2B data in natural language and trust what comes back Translate insights into a cohesive narrative and present technical findings to senior leadership and non-technical audiences Experience: Degree (or related work experience) with a focus in analytics, statistics, economics, computer science, or other quantitative fields 3+ years of experience in a data analytics or business intelligence role, ideally supporting a sales

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 People Analytics team at Lyft exists to build data trust — turning people data into clear, reliable insights that help our HR Business Partners, talent leaders, and executives make better decisions. We're a small, high-impact team in the middle of a meaningful BI transformation: we recently moved to ThoughtSpot as our primary analytics platform, and we're not just replicating old dashboards — we're rethinking what self-service analytics looks like for a People team. That includes exploring ThoughtSpot's AI capabilities to surface proactive insights, enable natural language querying, and reduce the friction between a business question and a data answer. There's real greenfield work here, and we're looking for someone who wants to help define what AI-powered people analytics looks like at Lyft. We're looking for a Data Analyst to join our People Analytics team, based in Toronto. You'll report to the Senior Manager, People Analytics and serve as the first point of contact for incoming data requests across the People organization — triaging, scoping, and delivering on analytical needs ranging from quick ad-hoc pulls to fully built ThoughtSpot dashboards. This role is well-timed: you'll be joining as we complete our migration from Tableau to ThoughtSpot, which means you'll have genuine influence over how we build our reporting layer and push into ThoughtSpot's AI features — think natural language search, AI-generated insights, and proactive anomaly detection applied to people data. This isn't a "maintain the dashboard" role. It's a chance to help build something new. You'll be a self-starter who is equally comfortable writing SQL and presenting findings to a VP. Responsibilities: Serve as the first point of contact for incoming data requests from across the People organization — scoping needs, setting

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. Responsibilities: Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft Evolve data model and data schema based on business and engineering needs Implement systems tracking data quality and consistency Develop tools supporting self-service data pipeline management (ETL) SQL and MapReduce job tuning to improve data processing performance Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions Experience: Bachelor's degree in Compute