Technical Partner Manager in Canada

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, an

Scale Labs, Research Scientist — AI Controls and Monitoring As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might: Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs; Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected; Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps; Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be

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

Scale Labs, Research Scientist — Frontier Risk Evaluations As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities; Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems; Publish evaluation methodologies and write technical reports for policymakers. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes. A track record of published research in m

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join AirSupport helps Airbnb employees stay productive wherever and however they work. Within AirSupport, Executive Support provides a dedicated, high-touch technology experience for Airbnb’s senior leaders and their Executive Business Partners. The team combines deep technical expertise, proactive support, and strong cross-functional partnership across office, remote, travel, event, and other approved environments. Executive Support owns the executive technology experience, working closely with engineering, security, infrastructure, AV, workplace, and other technology partners who own the underlying technologies. The Difference You Will Make As a Senior Executive IT Support Engineer, you will be one of the most senior technical individual contributors within AirSupport and a trusted technology partner to Airbnb’s executive population. You will combine hands-on technical expertise with strong judgment, proactive planning, and cross-functional leadership. You will own complex and sensitive executive technology issues through resolution, anticipate risks before they become disruptions, and lead improvements that make the executive experience more reliable and supportable. Your impact will extend beyond the issues you personally resolve. You will identify patterns in what Executive Support is seeing, connect them to broader employee technology priorities, develop recommendations, and influence the teams responsible for the underlying technology. You will help shape Executive Support technical direction, represent the support perspective in major technology decisions, and identify opportuniti

About the Role The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a VP / Director of Machine Learning Engineering to lead and build a high-performing team while staying close to the technical work. This is a hands-on leadership role: you will set the strategic direction for our recommendation, personalization, and ads optimization systems, including recommendation foundation modeling, and you will stay in the algorithms and the code, conducting deep dives into modeling components and guiding the hardest technical decisions yourself. You will tackle complex machine learning problems at scale and partner closely with cross-functional teams to ship solutions that measurably improve how hundreds of millions of viewers experience Tubi. What You’ll Do Lead, build, and grow a high-performing ML engineering team, fostering a culture of technical excellence, ownership, and rapid iteration. Define and drive the ML strategy and long-term technical roadmap for recommendation, personalization, and ads optimization, including recommendation foundation modeling, identifying opportunities for ML to shape Tubi’s broader product and business strategy. Stay hands-on: conduct deep dives into algorithmic components and systems, ensuring models are optimized for both performance and scalability across regions and product areas. Lead the design, development, and implementation of advanced recommendation systems and algorithms, contributing directly to the most challenging technical problems. Build and deploy robust, full-stack ML pipelines: data extraction, feature development, model training, testing, deployment, and serving. Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring

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

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

Role Overview We are seeking a Staff Simulation Engineer to build an end-to-end aerial autonomy simulation stack at DoorDash Labs. This is a highly technical, hands-on leadership role focused on defining and implementing the simulation architecture that underpins autonomy development, validation, CI/CD testing, and pilot training. You will operate as the technical authority for simulation: owning core architecture decisions, developing key components yourself, and setting engineering standards. You will build and mentor a small, high-caliber simulation team while remaining deeply involved in implementation and system design. This role is ideal for someone who has built simulation systems from first principles, understands simulator internals deeply, and is excited to create a world-class platform from scratch. Key Responsibilities Architect and implement an end-to-end simulation stack for aerial autonomy at DoorDash Labs.. Develop high-fidelity simulation capabilities, including: Flight dynamics modeling Contact modeling and constraint handling Sensor and perception simulation Autonomy software-in-the-loop (SITL) integration Design and implement scalable simulation infrastructure to support: Regression testing in CI/CD pipelines Continuous validation of flight autonomy and autopilot software stack Mission-level testing and scenario generation Build cloud-deployed simulation systems to enable large-scale parallel testing and pilot training. Partner closely with autonomy, controls, and aircraft teams to ensure simulation fidelity and validation alignment. Establish technical direction, architecture standards, and performance benchmarks for simulation. Mentor and grow a small team of simulation engineers while remaining deeply hands-on. Required Qualifications Master’s or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, or a related field. 10+ years of experience in robotics or physics-based simulation. Deep expe

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 have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role We're looking for an experienced technical operator to lead live testing, deployment, and operational validation of cutting-edge autonomous technologies. This role sits at the intersection of engineering and operations, helping ensure new capabilities are safely deployed, thoroughly evaluated, and translated into actionable engineering feedback. You’re excited about this opportunity because you will… Lead and oversee live testing across transport, deployment, and safety validation. Partner closely with hardware, software, and business operations teams to validate new product capabilities while providing guidance and mentorship to junior team members. Conduct and document complex tests for autonomous technologies, evaluating robot behavior, identifying issues, and validating new features and requirements. Provide actionable technical feedback to engineering teams based on test outcomes. Exercise technical judgment during live testing by evaluating robot behavior, assessing operational risk, distinguishing expected behavior from product defects, and determining when engineering escalation or additional validation is required. Develop and implement testing processes, protocols, and checklists that improve the safety, efficiency, and reliability of new products. Utilize internal tools to analyze logs, investigate issues, document findings, and track issues through resolution. Mentor junior team members in structured debugging and documentation practices. Conduct detailed analyses and generate comprehensive reports that identify trends, summarize findings, and provide strategic recommendations to engineering and operations partners. We’re excited about you because… 2+ years of exper

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We’re looking for dedicated, experienced, and deeply curious individuals to help solve some of the most complex challenges faced by our customers while building the future of post-AGI support alongside us. In this role, you’ll work directly with customers through support tickets and live calls, troubleshooting high-impact issues and resolving novel, often ambiguous technical problems in one of the fastest-moving environments in technology. As AI adoption rapidly accelerates, the work you do will directly support mission-critical systems being built on OpenAI’s platform, serving as a critical line of defense for customers operating at massive scale. Beyond resolving technical issues, you’ll help define what world-class support looks like in an AGI-driven future. You’ll partner closely with Engineering, Product, and Operations to improve systems, reduce bugs, and elevate the customer experience, while leveraging automation, agents, and our own AI technology to transform how support operates at scale. This Toronto-based role is currently remote and is expected to transition to an in-office arrangement. In this role, you will: Work directly with customers to troubleshoot and resolve their most complex technical issues, including API failures, integration challenges, authentication errors, and production incidents. Providing

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is building the next generation of intelligent agents powered by AI. We're seeking a Senior AI Agentic Engineer to lead this transformation across the enterprise. This is a strategic role for someone who can bridge the gap between AI technology and business value, designing and deploying AI-powered workflows that deliver measurable outcomes. You'll work across IT, people operations, marketing, sales, finance, legal, and procurement to architect AI-first solutions that solve complex business problems. Responsibilities: Architect and implement AI agents and intelligent workflows that transforms complex, multi-step business processes and deliver quantifiable business outcomes Partner with business leaders and stakeholders across multiple departments to identify high-impact AI opportunities that align with organizational objectives Elicit requirements from diverse stakeholders and translate complex business problems into technical solutions Build compelling business cases that clearly articulate ROI, implementation costs, benefits, timelines, and strategic alignment Evaluate, recommend, and implement AI solutions that best fit organizational needs and use cases Design solutions with an AI-first approach, ensuring optimal value delivery and user experience Monitor and measure the performance of AI workflows, using data-driven insights to demonstrate value and drive continuous improvement Design and deliver training programs, workshops, office hours, and enablement materials that help teams understand and adopt agentic solution Create frameworks, best practices, templates, and reusable patterns that accelerate AI adoption and ensure consistent quality Build a community of practice around AI and intelligent agents, empowering others to identify opportunities and contribute to the agentic roadmap Act as

Industrial Designer San Francisco, CA - Hybrid At IDEO, we use design to create new products, services, experiences; tangible strategies; and creative capabilities. IDEO San Francisco is in search of a new Industrial Designer to partner with interdisciplinary teams designing innovative and human-centered physical products and services. This role will own a hands-on workstream emphasizing creative problem solving, core industrial design skills, rapid prototyping and advanced visual storytelling. The ideal hire will champion hands-on making & prototyping, and collaborate fluidly with a wide variety of design professionals from communications design to UX researchers (and everything in between).This hire will have the unique opportunity to design cutting edge products, and grow as a Design Thinking practitioner within IDEO’s diverse network of Design Directors, Partners and Business Leaders. At IDEO, an Industrial Designer is responsible for independently executing components of highly complex client projects, showcasing advanced skills in user-centered physical product design . You will integrate form and function, while balancing user needs and technical considerations to create solutions that resonate with users and businesses alike. What makes a career at IDEO unique is our radical empathy and compassion for the user, always leading with creative confidence and collaborative rigor. You will work with world-class researchers, business designers, data scientists, and others disciplines outside of design, to push the edges of your craft, creating solutions that are as inclusive as they are transformative. We are especially excited to meet candidates with exceptional visual storytelling abilities, a drive to “get out from behind the screen” by prototyping in both digital and physical realms, and a grounding in design for manufacturing (DFM). This hire must be within a commutable distance of IDEO’s San Francisco studio. IDEO proudly supports flexible work. Onc

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 the Team DoorDash Labs, established in 2018, serves as the innovation hub for DoorDash, focusing on developing automation and robotics solutions to enhance last-mile logistics. The team's mission is to create technologies that support and augment human networks, aiming to improve efficiency for Dashers, merchants, and consumers alike. We’re ruthlessly focused on business impact. We are a highly senior team composed of former pioneers from a variety of different robotics industries. As of 2025, DoorDash has completed 10B lifetime deliveries. We’re focused on how to do the next 10B even better. About the Role We are seeking a highly motivated Senior Reliability & Test Engineer to join our team. This individual will play a key role in the development and validation of our unmanned platforms at the system and component levels. You will partner closely with EE, ME, and Autonomy teams to translate mission needs into robust, reliable hardware. The ideal candidate thrives in a fast-moving, cross-functional environment where reliability and test rigor determine program success. You will be hands-on in developing test methods and equipment to uncover failures before they happen in the field. You will partner closely with EE, ME, and Autonomy teams to translate mission needs into robust, reliable hardware. The ideal candidate thrives in a fast-moving, cross-functional environment where reliability and test rigor determine program success. You’re excited about this opportunity because you will… Architect and implement rigorous validation strategies, utilizing Python scripts for automation while leveraging CAD and shop tools to engineer bespoke test fixtures and hardware rigs. Oversee experimental execution across internal facilities and external laboratories, maintaining technical mastery over vibration tables, environmental chambers, DAQ systems, and ingress protection testing. Translate high-level vehicle reliability requirements into granula