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POSITION DESCRIPTION ROLE: ACCOUNT SUPERVISOR TEAM: ACCOUNTS LOCATION: TORONTO (HYBRID) 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 As an Account Supervisor, you’ll oversee a portfolio of mid-sized client accounts or multiple brands within a larger partnership, operating in a fast-paced, client-facing environment. You are both a trusted advisor to clients and a day-to-day leader for your team, balancing hands-on delivery with coaching and oversight. You’ll manage relationships, budgets, and cross-functional execution, ensuring every campaign phase delivers measurable value against client goals. You’ll proactively identify opportunities, risks, or efficiencies, bringing clarity and structure to complex, multi-channel programs. With a balance of strategic thinking, sharp communication, and calm problem-solving, you’ll lead integrated teams through shifting priorities with confidence and composure. Whether guiding junior colleagues, managing vendors, or preparing client strategies, you’ll bring initiative, adaptability, and integrity to every interaction—helping teams deliver great wor

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . About the team Dialpad's Contact Center QA team owns the quality of the AI-driven services behind our customer engagement platform. We validate that complex features like AI Routing, Digital Agents, and real-time Analytics are genuinely enterprise-grade in scale, reliability, and performance. And we go further, working cross-fun

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

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE: Are you passionate about driving innovation in the data storage industry? Are you skilled in crafting technical solutions that exceed customer expectations? If so, we have an exciting opportunity for you! Everpure (formerly Pure Storage), a leader in the data storage and flash technology space, is seeking a talented and motivated Senior Pre-Sales Systems Engineer to join our dynamic team. As a Senior Pre-Sales Systems Engineer, you will play a crucial role in understanding our customers' unique challenges and tailoring Everpure solutions to meet their specific needs. Collaborating closely with the sales team, you will act as a technical expert during the sales process, helping to showcase the value of our products and services. WHAT YOU’LL DO: Develop an exhaustive understanding of what drives a customer’s business and what motivates their decision making Connect the dots from technology solutions, inclusive of the Everpure portfolio and others from the ecosystem, to measurable customer business outcomes Partner closely with account managers, specialists and channel partners to create a seamless and holistic customer experience and strategy to drive revenue growth and net new business Delight customers and teammates with your technical leadership and domain expertise on storage products, distributed storage architectures, file systems, and competitive storage offerings in the DAS, NAS and SAN product spaces

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

Location: San Francisco, CA (Remote/Hybrid Available) What is Verse? The race to AI has become the race to power. Every breakthrough in artificial intelligence depends on one thing: access to electricity. But across the country, aging grid infrastructure and years-long interconnection queues are slowing the deployment of the data centers that will power the next generation of innovation. Solving this challenge isn't just about energy—it's about unlocking the future of AI. At Verse, we're building the energy intelligence platform for the AI economy. Our software helps the world's largest energy consumers achieve faster, cheaper, and cleaner power by combining real-time control of energy assets with complete visibility into their energy portfolio. Backed by Bessemer Venture Partners, GV, Coatue, and NVIDIA, and built by pioneers in grid-scale batteries, energy markets, and enterprise software, we're redefining how the world's most ambitious organizations access and manage energy. The Role You will be a member of the technical staff developing product experiences for our Dispatch Intelligence users – customers who want and have battery energy storage systems for additional energy cost savings or faster interconnection times. In this role, you will serve in a “full stack” capacity designing, building, and maintaining frontend and backend components of our energy storage suite of applications. We use Typescript, React, Next.js, Tailwind CSS, Radix/ShadCN, Jest, Cypress, Playwright, Vitest, and Storybook with Echarts and D3/Observable for data visualization for our frontend, and Cloudflare Pages for hosting and content delivery. We rely on identity and auth platforms like Clerk for sign-in flows. Our backend is written in Go and Python with Postgres/AlloyDB and blob storage for data persistence. Key Responsibilities Foster a culture and mindset of well-designed systems, test-driven software, and proactive communication with a high degree of transparency, mutual resp

Location: San Francisco, CA (Hybrid) What is Verse? The race to AI has become the race to power. Every breakthrough in artificial intelligence depends on one thing: access to electricity. But across the country, aging grid infrastructure and years-long interconnection queues are slowing the deployment of the data centers that will power the next generation of innovation. Solving this challenge isn't just about energy—it's about unlocking the future of AI. At Verse, we're building the energy intelligence platform for the AI economy. Our software helps the world's largest energy consumers achieve faster, cheaper, and cleaner power by combining real-time control of energy assets with complete visibility into their energy portfolio. Backed by Bessemer Venture Partners, GV, Coatue, and NVIDIA, and built by pioneers in grid-scale batteries, energy markets, and enterprise software, we're redefining how the world's most ambitious organizations access and manage energy. The Role We're seeking an experienced Senior Optimization Engineer to join our Data Science Team. In this role, you will lead the design, development, and deployment of optimization models that power our software platform across applications including electricity markets, renewable energy, and battery energy storage systems. You will be responsible for developing production-grade optimization engines that solve complex operational and planning problems at scale. This role requires deep expertise in mathematical optimization, strong software engineering skills in Python, and experience building optimization models that integrate with production systems. The ideal candidate has significant experience in the energy industry, particularly electricity markets and battery storage optimization. This position emphasizes technical leadership, ownership of complex optimization projects, and collaboration across engineering, product, and commercial teams to deliver high-impact optimization solutions. Key Res

Location: San Francisco, CA (Remote/Hybrid Available) What is Verse? The race to AI has become the race to power. Every breakthrough in artificial intelligence depends on one thing: access to electricity. But across the country, aging grid infrastructure and years-long interconnection queues are slowing the deployment of the data centers that will power the next generation of innovation. Solving this challenge isn't just about energy—it's about unlocking the future of AI. At Verse, we're building the energy intelligence platform for the AI economy. Our software helps the world's largest energy consumers achieve faster, cheaper, and cleaner power by combining real-time control of energy assets with complete visibility into their energy portfolio. Backed by Bessemer Venture Partners, GV, Coatue, and NVIDIA, and built by pioneers in grid-scale batteries, energy markets, and enterprise software, we're redefining how the world's most ambitious organizations access and manage energy. The Role As a Software Engineer focused on Fleet Telemetry & Control at Verse, you will be working closely with our energy solutions partners to design, implement, and test distributed energy resource controls and telemetry software on customer hardware at sites around the world. You will be part of a dynamic, high-performance team building applications directly on bare-metal or on hardware-level virtualization platforms. As an advanced technical leader in network programming and state management development, engineering teams will look to you for best standards and practices for interfacing with on-premises grid assets using solutions you will build and maintain. Key Responsibilities Foster a culture and mindset of well-designed systems, test-driven software, and transparent communication with a high caliber of mutual respect and consideration for stakeholders Mentor and support career and junior level engineers in their fleet telemetry and control software career development

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions. The next frontier for AI is the physical world. We're looking for an AI Product Manager to own the Robotics vertical within our Physical AI team. In this role, you'll own both the development of the data and training environments (the teleoperated demonstrations, real-world collections, simulated tasks, and annotation products that labs use to train and evaluate robot policies) and the "data as a product" strategy that powers them. You'll understand where physical AI is headed, decide what robot tasks and embodiments are worth collecting, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside robotics or physical AI research, and is able to pair that domain understanding with a sense for where current robot policies succeed and fail in real-world workflows. You'll translate that expertise into datasets, environments, and evaluation frameworks that teach robots to do real physical work, and you'll be the domain expert Scale's most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You'll Do Own the Robotics AI roadmap & data strategy: Set product direction for the robotics training stack and the data strategy behind it — what data we collect, on which hardware and embodiments, and what we source internally vs. through our marketplace. Establish a vision for where physical AI is heading, driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading physical AI labs to understand where their robot p

About Scale AI At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world’s most important decisions. We’re looking for an AI Product Manager to own the Finance vertical within our Agents Data & Reinforcement Learning Environments team. In this role, you’ll own both the development of RL environments (the realistic, high-fidelity simulations of financial software and workflows that labs use to train and evaluate agents) and the “data as a product” strategy that powers them. You’ll understand where AI is being used in the Finance industry, decide what financial tasks are worth modeling, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside the Finance industry, and is able to pair that domain understanding with a sense for AI research and current agent capabilities in Finance workflows. You’ll translate that expertise into environments and datasets that teach AI agents to perform real financial work, and you’ll be the domain expert Scale’s most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You’ll Do Own the Finance AI roadmap & data strategy: Set product direction for the Finance agents training stack and the data strategy behind it. Establish a vision for where AI is continuing to transform the Finance industry (including investment banking, private equity, public markets, corporate finance, FP&A, etc), driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading AI labs to understand where their Finance agentic capabilities fall short and shape new product lines and competit

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role Dialpad is looking for a Senior Engineering Manager to lead the team at the very core of the Dialpad experience: calling. Reporting directly to the VP of Engineering, you'll own the calling experience end-to-end: frontend, backend, and hardware devices (first-class desk phones, Room Phones, ATAs, and DECT solutions). Y