Technical Service Engineer in Canada

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in

We are building the Finance team to help make data-driven and financially sound decisions for Scale. The team is responsible for improving strategic, financial, and operational decisions by partnering with the leadership team in making critical decisions across Scale. The Corporate Finance team is responsible for owning the company’s budget, helping to drive monthly forecasts and annual planning processes, allocating and deploying the company’s resources efficiently, and performing financial analyses in partnership with all departments. As AI reshapes the competitive landscape, Corporate Finance sits at the center of decisions about where Scale invests, how quickly we scale, and which bets we make. You will have a unique opportunity to work closely with department heads on real-time, high-priority business issues and use quantitative insights to drive better decision making across Scale. The ideal candidate will not only have the technical skills to support their recommendations but also strong interpersonal skills to manage various stakeholders. What You’ll Do Provide analysis to support short and long-term decisions regarding workforce planning across the company. Own tools (such as the company's workforce planning system, TeamOhana) to automate and streamline reporting and headcount processes Partner cross-functionally with HR, Recruiting, Compensation, and Analytics teams to drive scalable analyses and insights. Define and maintain KPIs to measure impact on strategic initiatives and resource allocation. Manage the development, implementation, and administration of our financial forecasting system (Pigment) Partner with finance and accounting to drive process improvements (e.g. month-end close and reporting) Implement enhancements to forecasting tools, processes, and reporting deliverables that reduce manual work and improve data integration Support management, Board business, and financial planning, including presentations and key analysis requests Help execute

Scale’s Generative AI business unit is currently seeing historic levels of growth. As a Strategic Projects Lead (SPL), you will leading initiatives that will drive $XXM+ in new revenue for the business. This is a demanding role, and as an SPL, you should be prepared to wear many hats such as Operator, Product Manager and customer-facing Engagement Manager. The ideal SPL should have a strong entrepreneurial mindset, be comfortable getting into the weeds, and be excited about intense, impactful work that leads to an accelerated career progression. You will: Lead cross-functional projects with diverse stakeholders (Engineering + Ops + Go-to-Market) Partner with product and engineering teams to enhance products to fulfill needs of strategic customers and initiatives Own the execution of our data labeling operations for strategic projects Give regular progress updates to Scale’s executive team Work on some of the most impactful problems at the company Ideally, you’d have: Strong technical background (a degree in computer science is ideal, and at minimum the role requires the ability to do data analytics using SQL or Python). 2+ years of experience leading a team, developing product or operational processes, or as a SWE. Strong problem solving capabilities (experience working on operational challenges or as a consultant is a plus). Entrepreneurial experience and mindset - you are excited about building things from scratch 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 position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted e

National Security Hackathon Attendees – Stay Connected with Scale AI This posting is for candidates who attended National Security Hackathon and connected with a member of the Scale AI team. It was great meeting you at the Hackathon! Whether we spoke at our booth or on the floor, we always enjoy connecting with people who are passionate about advancing AI and machine learning. At Scale AI, our mission is to develop reliable AI systems for the world's most important decisions. For the past ten years, Scale has been the leading AI data foundry, supporting some of the most exciting advancements in AI, including generative AI, defense applications, robotics, and autonomous systems. We’re continuing to grow our team across a range of technical and mission-focused roles. If you're excited about the problems we’re tackling, feel free to share your information here. A member of our team will reach out if there’s a strong fit with one of our open opportunities. And even if the timing isn’t right today, we’d love to stay connected. We look forward to continuing the conversation. In the meantime, you can learn more about our work at scale.com . 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 position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: c

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. 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 position and may be inclusive of several career levels at Scale; it will be determined du

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

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

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

Come join our legal team to work on the most exciting legal, policy, and operational issues at the leading edge of AI. We're seeking strong product lawyers with specialized expertise in intellectual property law. As product counsel, you will advise on all legal aspects of product development, launch, and operations - including regulatory compliance, user terms, and risk management - while bringing deep expertise in your specialized legal area. The ideal candidate will have deep subject matter expertise in intellectual property law, a technology background, and a demonstrable history of providing practical product counsel to solve complex, time-sensitive problems in close partnership with cross-functional teams. This role reoprts to the Associate General Counsel, IP & Product. You will: Strategic Product Advice: Lead IP strategy for product development, embedding IP protection into the full product lifecycle from conception to commercialization, while also advising on related product and regulatory matters in collaboration with the broader legal team. Cross-Functional Collaboration: Partner with Research, Product, Engineering, Operations, Communications, and Marketing teams to mitigate IP risks in product development, data licensing, and open-source governance. IP Counsel: Support management of Scale's worldwide IP portfolio including patents and trademarks; assist with patent prosecution and trademark registration and enforcement. Risk Mitigation: Advise on third-party, synthetic, and open-source data and models, ensuring compliance with licensing requirements; design open-source governance policies. Agreements: Support drafting and negotiation of commercial agreement provisions involving intellectual property. Specialized Expertise: Provide counsel on machine learning, robotics, and other technical areas, with ability to engage effectively with technical teams on complex engineering and product issues. Training: Develop and deliver IP and data licensing trainin

As a member of our Frontier Tech Consultant team, you will play a critical role in advancing cutting-edge AI innovations by conducting high-impact experiments and ensuring seamless execution at the highest quality standards. Your work will directly contribute to Scale AI’s growth, shaping the future of artificial intelligence. In this role, you will be working on various types of projects, including but not limited to: research experiments, dataset generation, data quality improvements, and in-depth technical analysis. You will tackle complex, technical and operational challenges while collaborating closely with Scale’s ML research scientists and SPM team. The ideal candidate is analytical, detail-oriented, and results-driven, with strong problem-solving abilities and excellent communication skills. We are looking for someone who thrives in a fast-paced environment, is proactive in overcoming challenges, and is committed to delivering exceptional outcomes. If you are eager to contribute to the forefront of AI innovation, we encourage you to apply. You will be responsible for: Design and execute research experiments Build and evaluate frontier LLM datasets Develop training and testing material for frontier pipelines Improve quality of existing and new products Ideally you’d have: Strong machine learning knowledge, either by being in the final years of a ML PhD career or having already graduated Strong writing and verbal communication skills An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results Analytical, planning, and process improvement capability Experience working in a fast-paced, entrepreneurial environment Technical skills including familiarity with Python, GPU, AWS, API, LLM, ML, and SQL Pay: $60-80/hr Commitment: This is a fully remote, US-based part-time (10-20 hours per week), on-going contract position staffed via HireArt. HireArt values diversity and is an Equal Opportunity E

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Software Engineer, you will own the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Design and implement scalable backend systems for Federal customers using cloud-native AI infrastructure. Build features for agentic systems including multi-layered guardrails and data retrieval optimization. Develop data pipelines and machine learning infrastructure to make data sources accessible by agents. Collaborate with cross-functional teams to execute backend solutions for secure environments. Participate in customer engagements to understand requirements and deliver technical solutions. Define requirements with stakeholders and implement features until they are accepted. Contribute to the platform roadmap and product strategy for the Federal business. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes

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

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and contai

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. Join Tenstorrent as a Staff Reliability Engineer and help define the reliability strategy behind the next generation of AI computing systems. In this highly visible technical leadership role, you'll drive reliability from architecture through production, partnering across hardware, software, and manufacturing teams to build high-performance AI platforms that set the standard for uptime, durability, and quality. If you're passionate about solving complex engineering challenges and influencing products at scale, you'll have the opportunity to shape technology powering the future of AI. This role is hybrid, based out of Toronto, Canada. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You've spent 8+ years in reliability engineering, ideally in high-performance computing, AI hardware, or data center systems. You're comfortable with the statistical side of the job, HALT, HASS, ALT, MTBF, Weibull analysis, and FMEA are all familiar territory. You can work through a technical problem in a thermal lab and then explain the risks and trade-offs clearly to leadership. You're good at bringing people together, mechanical, electrical, thermal, softw

Director of Corporate Accounting Reports To: VP Finance Location: North America (Hybrid) Team: No direct reports Role Summary The Director of Corporate Accounting manages the consolidation, reporting, and systems data landscape for a multi-entity corporate group operating in Canada and the U.S. You will lead consolidations, multi-jurisdictional tax compliance, and technical accounting. Additionally, this role acts as the functional owner of the group’s financial technology, participating in the implementation of an electronic data warehouse for unified financial and statistical reporting, while establishing robust access management protocols for key financial systems. This is a hands-on leadership role. You will operate at both strategic and execution levels, ensuring audit readiness, controlled working capital, and consistent margin reporting across agencies. Core Mandate Deliver consolidated financial statements within the established group close calendar, with a business day five target as entity close processes mature Provide expertise on technical accounting matters Oversee global group taxation and manage the relationship with the group’s external advisors Responsibility for administration of core financial systems Mentor a growing team of accountants in an indirect relationship Key Responsibilities Financial Reporting & Consolidations Manage the month-end, quarter-end, and annual financial consolidation for 10-15 corporate entities. Oversee multi-currency consolidations, intercompany eliminations, and translation adjustments between CAD and USD. Prepare accurate, timely consolidated financial statements, management reports, and variance analyses for senior leadership and the Board of Directors. Serve as the primary contact for external auditors, managing the annual audit process and supporting audit readiness and the timely resolution of findings and control deficiencies. Financial Data Warehouse Participate in designing, implementing, and mai