Internal Audit Analytics Associate Manager in Canada

Here's a summary of the role: Identity infrastructure is not glamourware . It doesn't get standing ovations at company all-hands. But it is the thing every product in the portfolio depends on, and when it breaks, everyone knows. If you're the kind of PM who finds that genuinely interesting, read on. This role is for someone who has lived inside SAML flows, argued over PKCE token lifetimes, and knows exactly why SSO bypass lists are a necessary compromise. You'll own the authentication platform that thousands of enterprise customers trust, and you'll shape it alongside engineers who go deep. No surface-level roadmap ownership here. Here's a breakdown of what you'll do (not all of it, just the important stuff) Own the product strategy and roadmap for core authentication flows: SAML 2.0, OIDC/OAuth 2.0 with PKCE, MFA enforcement, token lifecycle management, and multi-IdP federation. Make product decisions that sit at the intersection of system design, security architecture, and developer experience, working directly with senior engineers on protocol choices and infrastructure trade-offs. Drive adoption of platform identity capabilities across internal engineering teams through influence, moving products toward modern API patterns and away from legacy integration surfaces. Use AI coding tools (Claude Code, Cursor, or similar) to prototype ideas and validate concepts before you pitch them; this is expected, not optional. Track the IAM standards landscape, including passkeys, FIDO2, SCIM, zero-trust, and verifiable credentials, and use that knowledge to sharpen product direction. Translate complex authentication concepts (JWT structures, SAML assertions, PKCE handshakes) into clear specs, user stories, and prioritized backlogs for audiences from engineers to executives. These are the essentials you'll ne

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

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

Owns day-to-day deal pricing execution for Enterprise, including pricing calculations, staffing inputs, and dashboard reporting that gives Sales and Deal Desk leadership visibility into deal status, pricing, and margin. Partners with the Deal Desk Manager on customer deal structuring and on identifying ways to accelerate the deal approval process. What You’ll Do Deal Pricing Execution Manages day-to-day deal pricing calculations for Enterprise deals, including ROI modeling and EPD staffing inputs Applies existing pricing frameworks consistently across Land, Expansion, and Framework deals Partners with the Deal Desk Manager to design customer-specific deal structures for non-standard or complex deals Pricing & Deal Status Reporting Builds and maintains a pricing dashboard tracking deal status, pricing, margin, and overall deal health across the Enterprise pipeline Updates pricing and trend reporting to keep leadership current on where deals stand and how pricing is trending against targets Process Optimization Identifies bottlenecks in the deal review & approval process and proposes ways to accelerate cycle time Helps standardize and streamline recurring pricing/approval steps into repeatable, lower-friction workflows Tracks deal approval cycle time and surfaces trends to inform process improvements Cross-Functional Deal Coordination Owns deal crafting end-to-end from initial pricing/modeling through contract review, coordinating with sales management, reps, and internal stakeholders Ensures the relevant stakeholders (Accounting, Finance, EPD, Legal) review and approve deals at the appropriate stage before they progress Routes deal packages to the correct reviewers and tracks open items so deals aren't stalled waiting on sign-off Strategic & GTM Support Tackles ambiguous, open-ended questions around Scale's go-to-market motion and iterates quickly on solutions that deliver measurable results Supports Sales and Finance leadership in quarterly strategy and

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

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. Our Approach As part of the interview process, you’ll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale. Responsibilities: Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal Collaborate closely with internal operators (your use

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

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. We are seeking a hands-on Data Center Technician, IT Contractor to support the installation, deployment, relocation, cabling, inventory, maintenance, and decommissioning of servers, network equipment, storage systems, and other IT infrastructure. The successful candidate will follow established procedures, maintain accurate documentation, and coordinate effectively with internal technical teams and data center personnel. This role will be a 6-month contract fully on-site, based out of the downtown Toronto, ON Beanfield data center, with travel to Tenstorrent office locations and other data center facilities as required. 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 You bring approximately 2 to 5 years of hands-on experience in data center operations, IT infrastructure, server or network hardware, or a similar technical role. You are comfortable working with servers, network equipment, storage systems, racks, rack layouts, and copper and fiber optic cabling. You are detail-oriented, organized, and able to follow documented procedures, cabling standards, installation instructions, and safety requirements. You communicate clearly, work well wi

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. At Tenstorrent, we are building open, scalable compute for real AI workloads. As Director, Customer Hardware Engineering, you own the technical relationship with strategic customers and FAEs, turning their silicon needs into precise requirements for our hardware and software teams. You connect customer architectures to Tenstorrent platforms so their models run efficiently on our silicon. This role is hybrid, based out of Toronto, Austin, TX or Belgrade, Serbia. 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 leader of customer-facing technical teams and Field Application Engineering organizations. Strong background across RTL, verification, and physical design for custom silicon programs. Systems thinker who understands how RTL choices affect software, performance, and customer solutions. Clear communicator who aligns customers, FAEs, and internal teams around shared technical goals. What We Need Own technical customer relationships and convert high-level asks into concrete engineering specifications. Coordinate with hardware and software leads on customer-specific NEO silicon configurations. Oversee RTL changes and NEO cus

ROLE: MEDIA ACCOUNT MANAGER TEAM: MEDIA LOCATION: TORONTO (HYBRID 2X/WEEK) COMPANY OVERVIEW At Salt Media , we're on a mission to earn the world's attention. As the media division of Salt XC, we're building a different kind of agency where media, commerce, creative, data and technology work as a single connected team. Our people combine strategic thinking with AI-powered tools, automation and advanced analytics to help some of North America's most recognized brands solve complex business challenges and drive measurable growth. We move quickly, challenge convention, and believe the best ideas come from curious people who are empowered to experiment. If you're looking to do career-defining work alongside smart, ambitious teammates in an environment that's shaping the future of media, we'd love to meet you. ROLE OVERVIEW As an Account Manager at Salt Media, you’ll take day-to-day ownership of client accounts or campaign workstreams, keeping delivery on track while building trusted relationships with client contacts. You’ll work closely with an Account Supervisor or Director to execute against the account strategy, translating plans into clear, well-managed execution. You’ll manage the moving pieces of a campaign or account — timelines, budgets, vendor coordination, and status reporting — while flagging risks early and keeping internal and client stakeholders informed. You’ll also start to build your own point of view on the account, contributing ideas for organic growth and supporting the planning behind key client moments like QBRs. You’re organized, detail-oriented, and comfortable managing multiple workstreams at once. You communicate clearly, take ownership of your work, and are eager to grow your account management craft — building the judgment and client presence that will carry you toward an Account Supervisor role. CORE RESPONSIBILITIES Project & Operational Management

ROLE: SENIOR DIRECTOR, SOCIAL & CREATIVE STRATEGY DEPARTMENT: CREATOR & SOCIAL LOCATION: TORONTO, HYBRID ONSITE COMPANY OVERVIEW Salt is a North American marketing agency that creates connected experiences through creative, digital & media innovation. Our mission is to “Earn The World’s Attention” and Salt is built to find, develop, execute, and amplify the ideas that are worthy of our clients’ audiences. We’ve structured our agency to do what’s right for our clients – to connect different perspectives, to work across mediums, and to focus on delivering meaningful, effective results. We’re committed to living up to the values in our name. “Salt of The Earth” means we value collaborative, humble, hard-working people here. We’re looking for people who are as smart as they are kind because we believe the right talent and the right culture help us do what’s right for our clients. ROLE OVERVIEW We are looking for a hybrid social strategist who balances creative vision with deep analytical rigor to guide our social and creator-led initiatives. In this role, you will act as the strategic engine for client accounts—building sharp social playbooks, scoping complex programs, consulting and collaborating with internal teams and translating performance data into clear creative direction and effective strategy . We are looking for someone who understands social because they have actively helped shape brands’ social presences, understand how to identify culturally relevant opportunities, kn ow how to source strategic creator partners, cultivate communities, and evolve a brand’s social approach in real time based on data and insights. You will consult closely with our influencer execution team on strategy and creator alignment (without managing day-to-day execution ) and provide strategic and creative leadership to our internal social and creator teams The ideal candidate b

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

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term. If you want to work on commercializing autonomy and robotics in a service used by millions of people — and on bringing the merchant partners who power that service along with us — then we want to talk to you! About the Role Come help us redefine last-mile logistics through robotics, automation, and other advanced technologies. Autonomy only works when merchants — restaurants, retailers, and other partners — can reliably interact with our robots: handing off orders, troubleshooting edge cases, and trusting the experience enough to keep using it. This role owns that side of the equation. We're looking for a Merchant Success & Growth lead to build the strategy and operational mechanisms that get merchants onboard, keep them performing, and turn their day-to-day reality into a tight feedback loop for product and engineering. You're excited about this opportunity because you will… Own merchant adoption and performance KPIs for autonomy end-to-end — defining what "successful merchant interaction with a robot" means, instrumenting it, and driving improvement against it. Build the playbooks and operational mechanisms to onboard merchants to autonomy — from first conversation through training, go-live, and steady-state ops — and scale them across markets. Partner with sales, account management, and field ops to recruit and ramp the right merchant cohorts for each stage of the product, and design experiments that test new merchant-facing features and handoff models. Define merchant performance benchmarks (handoff success rate, dwell time, dasher/robot interaction quality, merchant CSAT) and run the cadence that holds partners and internal teams accountable to them. Stand up the feedback loop from the field back to product and engineering — turning merchant complaints, edge cases, and frontline observations into prioriti