Field Sales Executive in Canada

Who We Are HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless. We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work. Join us as we reinvent work, so people everywhere can do their best work. About The Role HP IQ's Connectivity team is seeking an Embedded Firmware Engineer with strong hands-on experience across RTOS and embedded Linux platforms. You'll bring up new hardware, develop and support firmware across core device subsystems, and help scale products from prototype to fleet deployment. A key part of this role is enabling on-device intelligence — bringing AI models, sensing algorithms, and local processing to lightweight, power-constrained devices at the edge. What You Might Do Design, develop, and debug firmware across RTOS and embedded Linux platforms. Lead hardware bring-up — board bring-up, driver integration, and firmware support through to production. Develop and maintain firmware for subsystems such as connectivity, power and other sensors. Integrate lightweight model inference and sensing/proximity algorithms within tight compute, memory, and power budgets. Support fleet-scale deployment: OTA updates, field diagnostics, and post-launch sustainment. Collaborate with hardware, systems, and QA teams to troubleshoot system-level issues and drive root-cause fixes to closure. Ess

We're looking for a Customer Success Manager with a deep understanding of analytics and business intelligence to join our team. This role is critical for ensuring our customers maximize the value they derive from our platform, with a direct focus on improving Net Dollar Retention (NDR) through strategic account management and growth initiatives. This is an in-office role based out of the San Francisco office. Key Responsibilities: Strategic Account Management: Build and maintain strong relationships with decision-makers and influencers within our customer base, with a focus on high-value accounts. Analytics Expertise: Leverage your deep understanding of analytics and business intelligence to guide customers in optimizing their use of Sigma Computing's platform. Help them understand their data and gain actionable insights. NDR Growth: Develop and implement strategies aimed at maximizing NDR. This includes identifying opportunities for upselling and cross-selling, as well as reducing churn through proactive engagement and solution-oriented support. Customer Advocacy: Serve as the bridge between our customers and our product team. Advocate for features, enhancements, and integrations that will drive customer satisfaction and retention. Success Plans: Collaborate with customers to develop and execute success plans that align Sigma Computing's capabilities with the customer's business goals and objectives. Educational Initiatives: Design and deliver training sessions, webinars, and workshops to increase product knowledge, adoption, and engagement among our user base. Required Skills / Experience: Bachelor’s or Master’s degree in Business, Analytics, Computer Science, or a related field. 4+ years of experience in a customer success, account management, or consultative role within the SaaS, analytics, or business intelligence industry. Strong analytical skills with a proven ability to solve complex problems using data. Excellent communication and interpersona

Director of Engineering, Physical AI Role Overview The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment. This role requires significant ownership in a fast-paced environment and you will motivate internal teams to set the pace for business growth. Travel will come into play. Key Responsibilities: Set and drive the technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research Lead a multidisciplinary engineering organization—spanning engineering managers, software engineers, ML engineers, and ML research scientists—while designing the organizational structure, talent strategy, and culture required to scale rapidly without compromising on quality or strategic alignment Maintain exceptional technical and operational excellence by deeply understanding team deliverables, asking incisive questions, identifying slipping standards early, and knowing precisely when to step in Drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities Collaborate with researchers and clients to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads Required Qualifications: Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field 8+ years of engineering experience in fast-paced environments, including 4+ years direct people management demonstrated history of recruiting, mentorin

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 are hiring a Software Integration Engineer for our Platform Integration team. This is a critical role with impact across the robot lifecycle, from manufacturing to daily operation. The Platform Integration team owns making sure the robot works as one cohesive system. The focus is on the interfaces between subsystems; this role in particular is focused on the software side handling interaction between: OS & software stack; firmware; networking; timing; and calibration. In this role, you will work cross functionally with our electrical, hardware, firmware, and autonomy engineers to support new functionality both in both hardware and software. This includes creating provisioning tools, functional tests, and supporting integration into the autonomy software stack. You will report to the Autonomy Platform Lead on our Autonomy Platform Team at DoorDash Labs. We expect this role to be hybrid with some time in-office and some time remote. You’re excited about this opportunity because you will… Play an integral role on a small and focused team. Lead system-level debug when an issue crosses subsystem boundaries or no single team can isolate it. Support early integration of new sensor and software component designs by identifying interface requirements, risks, dependencies and required checks. Design and maintain integration tests, test setups, and procedures to ensure subsystems, once combined, satisfy requirements and design intent. Build and maintain the mission-readiness checks used before manufacturing signoff, validation, field testing, or mission use for different robot platforms. Create the tools, checks, and debug guidance that Manufacturing Integration, Validation,

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 are hiring a Firmware Validation & Integration Engineer for our autonomy software team. This is a critical role to build robust and scalable validation for our firmware and systems to ensure reliability at every level. In this role, you will work with our electrical, firmware, and autonomy engineers to build the infrastructure and test suites required to validate the system. This includes designing and implementing our Hardware-in-the-Loop (HIL) simulation environments and automation frameworks from the ground up. You will report to the Autonomy Platform Lead on our Autonomy Platform Team at DoorDash Labs. We expect this role to be hybrid with some time in-office and some time remote. You’re excited about this opportunity because you will… Play an integral role on a small and focused team. Design and build Hardware-in-the-Loop (HIL) systems to simulate vehicle dynamics and sensor data for comprehensive firmware and system-level validation. Develop automated test infrastructure and software tools to exercise multiple embedded platforms throughout our robot system. Interface many layers of our control system including vehicle controls, power management, and motion control to ensure seamless system integration. Implement low-level test sequences and validation algorithms to safely stress-test vehicle components such as batteries, drive-train, and thermal management devices. Collaborate with cross-functional teams to identify edge cases and hardware-software corner cases that impact vehicle safety and performance. We’re excited about you because… BS/MS degree in Computer Science, Robotics, Electrical Engineering, or related technical field. 5+ years of experience in validati

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The Role: We are seeking a highly skilled and experienced Staff Software Engineer to join our Test Platform team. In this role, you will have the opportunity to directly impact the design and architecture of our Developer Platform and tooling that enables SoFi engineers to create and deliver high-quality solutions. You will collaborate and partner with a curious team of engineers to design and deliver solutions that raise the testing and reliability standards for our backend and web applications. This new team will be focused on building a green field project to enable autonomous testing for our AI driven SDLC, leveraging cutting edge technologies to deliver a highly resilient and thorough platform. If you are a seasoned Staff Software Engineer with a passion for building products that just work and enabling developers to build reliable services, and a strong background in distributed systems, we invite you to apply for this exciting and new opportunity. What You’ll Do: Provide technical leadership for initiatives in Testing and Reliability, with a focus on integrating AI-driven automation and autonomous testing practices. Collaborate with product engineering teams to understand requirements and design platform capabilities that are efficient, robust, and developer-friendly. Architect and implement solution

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Enterprise AI Pod is a forward-deployed, field-first unit within Instacart's Enterprise Solutions team — purpose-built to take the Instacart Intelligence Platform to market with B2B retail and CPG partners. As the AI Engagement Manager, you are the operational backbone of the engagement — the person who makes complex, multi-stakeholder AI engagements actually move. This is an orchestration role, not a commercial one; success is measured by getting partners to value, not by signings or P&L. You own the partner relationship from discovery through workflow adoption, hold the team accountable to delivery, and serve as the primary bridge between field execution and R&D — all while managing multiple engagements simultaneously in an environment where the playbook is still being written. About the Job Own the full AI engagement arc . From first d

Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Design state-of-the-art ML models and large-scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints. Design systems to speed up the time from idea to deployment of new models. Experiment and iterate on ML models (using tools including PyTorch and TensorFlow) to achieve key business goals and drive efficiency. Develop pipelines and automated processes to train and evaluate models in offline and online environments. Integrate ML models into production systems and ensure their scalability and reliability. Collaborate with product and strategy partners to propose, prioritize, and implement new product features. Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus two (2) years of experience in Building and shipping ML systems in production. Must have two (2) years of experience in each of the following: ML algorithms and model architectures; Designing, training and evaluating machine learning models; Productionizing and deploying machine learning models at scale; Orchestrating data pipelines and leveraging large-s

Role Summary Scale builds AI applications for organizations where reliability, security, and measurable results matter. Our core platform, SGP, gives teams the capabilities to build, deploy, evaluate, and operate those applications in customer environments. We're looking for a product leader to own the strategy and roadmap for SGP's core platform and lead the PM team responsible for it. You will work with customers, platform engineering, and forward deployed teams to build capabilities customers need, productize work developed in the field when it has broader value, and improve how teams build, deploy, and operate AI applications. This is a hands-on leadership role. You will connect work across teams into a coherent product, make difficult scope and investment decisions, and stay close enough to the details to know whether what we ship works for the people using it. What you'll do Own the platform strategy and roadmap. Prioritize across developer experience, capabilities customers need, and productizing work built in the field where it has broader value. Sequence investments against customer value, commitments, and dependencies. Define how the product should work. Work with users and engineers to write clear requirements and vibe code prototypes, user journeys, and measure success through customer outcomes, capability adoption, delivery time, and production performance, and follow through on gaps after launch. Align teams across the business. Work with platform engineering, forward deployed PMs, and business leaders to agree on shared capabilities, rollout priorities, and necessary differences across environments. Make clear what is available, where it works, and what remains to be delivered. Build and lead a strong PM team. Establish clear ownership across related product areas, hire and coach PMs, and raise the quality of product thinking and written requirements. Stay directly involved in the most consequential decisions. What we're looking for A track record of

Sigma is transforming how businesses run by delivering a high performance platform on the modern data architecture. As we grow the engineering team, we are looking for engineering leaders who want to build great products, devising product development, prioritization and execution strategy as well as developing a strong team providing career development, coaching, mentoring, performance evaluations, developing promotion cases, and other managerial responsibilities. About the role: We are looking for a self motivated, engineering leader eager to lead engineering teams with high performing engineers. You will need to be comfortable working in a fast-paced environment and support your teams to deliver incrementally against our roadmap. What you will be doing: Collaborate with cross-functional groups, executive team, field teams to devise business impact product strategy Enable the team to realize their potential and set them for achieving their career development goals Own execution and delivery of roadmaps, to help setup the business and your team for success Partner with the staffing team to recruit and build performing team Instill a strong sense of ownership and accountability within the team wherein members hold each other to a high bar Participate in discussions pertaining to the architecture and implementation techniques to represent, translate and optimize user directives into optimized queries You: Love working with world-class engineers, product managers, and architects to solve complex problems and enable business impact Have 5+ years of technical experience and 2+ years of people management experience Are opinionated and have great product sense make data driven decisions when unblocking the business Have hired, and developed high performing engineering teams Are curious, love to learn and to dig into new technologies to apply them when solving technical challenges Have demonstrated strong technical architecture and engineering skil

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 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

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

About the Team The DoorDash Research Fellowship is a 3-month program (extendable to 6 months) looking for Summer and Fall 2026 cohorts, for researchers and engineers who want to work on the hardest applied ML and AI problems in local commerce. Fellows are given the resources, autonomy, and access to real-world operational data needed to pursue ambitious research directions — with the goal of producing work that influences both the field and how DoorDash operates at scale. This program is modeled on the best external research fellowships: fellows are treated as independent researchers, not as junior employees on a product team. You pick the problem (within a set of priority areas), you own the direction, and you publish or ship the outcome. You’re excited about this opportunity because you will receive… Dedicated compute allocation sized to the research agenda — GPU clusters for training and inference budgets for experimentation Full access to DoorDash's research infrastructure — our internal RL stack, training and evaluation pipelines, RL environments built on real operational systems, agent evaluation harnesses, and the tooling our own research teams use day-to-day. Fellows are first-class users, not sandboxed visitors. Access to DoorDash operational data — real-world datasets spanning logistics, merchant operations, consumer behavior, and marketplace dynamics, under appropriate data governance Research mentorship from senior researchers and engineering leaders at DoorDash, plus a named research sponsor for each fellow who meets with you weekly and is accountable for unblocking your work Speaker series featuring leading researchers and practitioners from academia and industry — faculty from top ML programs, research leads from frontier AI labs, and senior operators from across tech. Fellows get dedicated 1:1 time with speakers when possible. A cohort of fellows working alongside you — a small, tight-knit group of researchers tackling different problems but sharing