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Location: Hong Kong Nex is on a mission to help families rediscover the joy of movement. Created by parents for parents, Nex combines technology and play to deliver fun, social, and interactive experiences powered by natural body motion, encouraging kids and adults to move more, play more, and have fun together. Nex Playground, the company’s award-winning active play system, is purpose-built to get families moving year-round, with safety and privacy as core considerations in its intentional design. It is certified kidSAFE+ COPPA compliant and built to support healthy, active play for all ages and abilities. Nex Playground features a growing library of 50+ experiences, including motion and dance games, fitness and educational experiences, and Nex Originals. Content includes collaborations with partners like Hasbro, Sesame Workshop, and NBCUniversal. Nex has been recognized by Fast Company’s Most Innovative Companies, TIME’s Best Inventions, and Parents’ Best Entertainment System for Families, and has earned Red Dot, IDEA, and Core77 international design awards. We encourage you to explore Have Fun and Is Motion Gaming Back? , as they offer a deeper look into our culture, values, and explain how our approach to motion gaming differs from previous generations. Nex employees may be expected to collaborate with colleagues across different time zones. Depending on the role and location, occasional travel may also be required for company events, external meetings, and other business-related activities. Important Notice: ⚠️ To protect yourself from recruitment scams, please note that Nex communicates through official company emails ending in @nex.inc . If you receive a suspicious email or message, please do not respond and report it immediately to us. Location: Hong Kong This is an initial two-month, part-time engagement, with potential for extension subject to performance, business needs, and mutual agreement. The Role Nex creates active-play experiences that bring people together through movement and games. Working with our Core Technology team, you’ll build and refine electronics and enclosures, collaborating with software engineers and researchers to turn concepts into reliable, usable prototypes. This is a hands-on prototyping role, not a mass-production hardware program. The Mindset You’re a practical builder, comfortable with schematics, soldering, CAD, and testing. You balance speed with engineering discipline, make sensible build-versus-buy trade-offs, and take ownership of the complete prototype. What You'll Do Design and modify circuits and PCBAs; select and integrate components. Create mechanical CAD, 3D-printed enclosures, and practical mounting solutions. Assemble, bring up, rework, and debug prototypes using lab measurements. Collaborate on firmware and software integration, resolving interface, connectivity, and power issues. Iterate quickly from test findings and build consistent, reliable prototype units. Document schematics, PCB files, BOMs, CAD, assembly instructions, and known limitations. Success Looks Like Fast iteration from identified problems to tested improvements. Usable, consistent prototypes that withstand repeated testing and handling. Clear documentation enabling the team to maintain and reproduce builds. What You Bring Demonstrated experience building working electronic prototypes, including circuit design, board bring-up, soldering, rework, and debugging. Hands-on experience with mechanical CAD and rapid enclosure prototyping, such as 3D printing. Experience integrating microcontrollers, sensors, wireless modules, and battery-powered electronics. Confidence using oscilloscopes, multimeters, logic analysers, and other practical debugging tools. Ability to work independently, make sensible trade-offs, and deliver within a short iteration cycle. Clear communication and documentation skills, including explaining issues and options to software engineers. Availability to work on-site in Hong Kong on a half-time basis for a two-month engagement. Preferred Experience with Bluetooth-connected devices, sensors, or interactive hardware. Embedded C/C++ skills and experience modifying firmware for device bring-up and diagnostics. Experience with compact, battery-powered consumer-device prototypes. Familiarity with component sourcing, PCB fabrication, and local rapid-prototyping suppliers. Experience preparing hardware for hands-on user evaluation. Interest in games, physical interaction design, or consumer electronics. If you are interested in this position, please share your CV and examples of hardware you’ve built—photos, videos, or brief write-ups are welcome. Describe your contribution, a problem you solved, and how you tested it. Include your availability, proposed schedule, and contractor rate. We Offer Competitive compensation package. Flexible working hours and vacation policy. Product-driven culture that treasures talents and individual growth. Front-row seat and hands-on experience with cutting edge technologies in the evolving gaming field Nex is located in San Jose, California, USA and Hong Kong . Learn more about us at https://www.nexplayground.com/about . We encourage applications even if you don’t meet more than 50% of the requirements — we believe that experience comes in many forms! Nex is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, gender identity, and sexual orientation), national origin, ancestry, age, physical or mental disability, medical condition, genetic information, marital status, military or veteran status, or any other characteristic protected by applicable law. This policy applies to all individuals at every stage of the employment relationship, including all current and prospective employees, and covers all employment decisions including recruitment, hiring, job assignment, promotion, compensation, benefits, training, discipline and termination. We are committed to providing a workplace free from discrimination and harassment and to fostering an inclusive environment for all employees.

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. We're looking for a Staff Engineer, Robot Learning to lead engineering for our real-to-sim product within the Embodied AI group. One of the fundamental problems facing autonomy teams is the sim-to-real gap in visual-spatial understanding, and we're applying decades of experience encoding the world precisely as it is to build the scalable real-to-sim stack for embodied AI. Working alongside the group's General Manager and Product leader, you'll inform the roadmap, own the technical requirements our researchers and engineers build against, and personally prototype and evaluate the changes you propose. You've lived the problems our customers are solving: you've trained and deployed embodied AI systems, seen where and why simulation fails to predict real-world performance, and worked through the consequences. This is not a role for someone who wants to manage and not ship, or someone who wants to ship without ownership of commercial consequences. This is a role for an entrepreneurial tech lead who loves to build and is energized by helping those around them do the best work of their lives. You have a co-founder mentality. You may have been part of a founding team before, or want to start your own business one day. What You'll Do - Sharpen the Roadmap - Bring first-hand knowledge of customer pain, existing solutions, and the value of doing better to roadmap decisions, and help focus effort on the most consequential problems to solve. - Own the Technical Requirements - Guide the team to design the real-to-sim stack pragmatically. Make the final recommendation on what to build, integrate, and simplify, ensuring capabilities work within customers' existing training and evaluation workflows. - Benchmark the Impact - Working with our Real-World Test Lab, design and run reproducible evaluations that measure the impact of our real-to-sim stack on policy transfer and real-world performance against customers' existing approaches. - Build and Ship - Lead engineering delivery and personally build critical features. Keep scope tight, remove blockers, and get performant capabilities into customers' hands quickly. - Raise the Technical Bar - Set a high bar for the team's work and deepen its understanding of robotics development and deployment, driving incremental improvement every week. What You'll Bring - Experience training, evaluating, and deploying robot policies in systems used by enterprise or government customers, with responsibility for performance in real operating conditions. - Deep practical experience using simulation for policy training or evaluation, including tools such as NVIDIA Isaac Sim, Isaac Lab, MuJoCo, or equivalent. You have diagnosed sim-to-real failures and understand when greater fidelity improves outcomes. - Hands-on experience with reinforcement learning, imitation learning, or both, and with deep-learning frameworks such as PyTorch. - A practical understanding of how visual perception and 3D scene representations affect robotics training, evaluation, and real-world performance. - Experience running experiments on real robots, from an ambiguous hypothesis through to defensible results. - Strong Python and C++ skills, with experience building reliable production software. - A bachelor's degree or higher in a relevant field. Nice to Have - You've authored or maintained a public robotics benchmark. - You've helped take an early product to repeatable adoption across multiple customers. - You've built or substantially extended robotics simulation infrastructure, including scene authoring, domain randomization, or large-scale training and evaluation. - You've trained and deployed vision-based navigation or mobility policies, particularly in varied, unstructured environments. - You've built pipelines that turn real-world reconstructions into simulation-ready environments. Competencies - Always Learning. Staying on top of the latest academic breakthroughs and commercial advancements, particularly in real-to-sim-to-real. - Relentless bias for action. You make decisions and ship as if the company’s success depends on it, because it does. You set the pace, and drive the people around you to rise to it. - Intellectually honest. You know there’s just one job that underpins every other in a startup: find the truth. You are relentless in your pursuit of it, including when it challenges your own convictions, and you raise concerns when you see them — even when it's uncomfortable, and especially when it's unpopular. - Pragmatic. You have no patience for not-invented-here syndrome and analysis paralysis. You find the fastest path to delivering customer value without going through one-way doors that undermine future scaling. - Confident and credible with customers. You can sit alongside an autonomy engineer and help them get to the root of their problems. You are comfortable speaking to customers and bring commercial nous to those discussions. Compensation & Benefits The expected salary range for this role is $270,000 – $300,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: United States Location & Work Arrangement Costa Mesa, CA (On-site) preferred Remote opportunities may be considered for exceptionally strong candidates located elsewhere in the U.S. Employment Details Contract: 6 months, with potential for extension or conversion to a permanent position Target Bill Rate: Up to $120/hour Requirements Must be a U.S. Citizen Must be eligible to obtain and maintain a Top Secret security clearance What You'll Do · Own thermal design and analysis for integrated hardware products, including drones, aircraft, missiles, or related defense systems. · Use first-principles engineering judgment to determine the right level of analysis for each design decision, including hand calculations, spreadsheets, MATLAB / Python models, FEA, and CFD. · Define thermal architectures that can withstand rugged environments, demanding flight envelopes, and operational edge cases, including hot, cold, transient, and mission-specific thermal conditions. · Partner with electrical, mechanical, aerospace, software, and systems engineers to document power dissipation, operating modes, thermal constraints, and design tradeoffs. · Build and maintain thermal FEA / CFD models to predict system performance, establish design limits, and define red / yellow operating thresholds for test and field use. · Define and execute prototype builds and thermal tests, including CAD support, sensor selection, DAQ setup, data post-processing, and results documentation. · Present thermal status, risks, tradeoffs, timelines, and recommendations in internal design reviews and customer-facing technical reviews. · Develop internal tools, workflows, or analysis methods that improve speed, consistency, and quality of thermal decision-making. · Support failure reviews and root-cause investigations using test data, thermal analysis, and first-principles reasoning. Required Qualifications · MS or PhD in Mechanical Engineering, Aerospace Engineering, Applied Physics, or a related field with a focus on heat transfer, fluid dynamics, thermal sciences, or thermal systems. · 5+ years of experience designing, analyzing, or validating thermal systems for integrated hardware products. · Strong first-principles understanding of heat transfer and fluid dynamics, including conduction, convection, radiation, fluid flow, and transient thermal behavior. · Experience supporting thermal design for aerospace, aircraft, rocket, missile, UAV, defense, or other high-performance hardware systems. · Experience using thermal analysis, modeling, simulation, and/or physical test data to drive design decisions for passive or active thermal management systems. · Ability to communicate technical tradeoffs clearly across engineering, program, and customer stakeholders, and ability to obtain and maintain a U.S. Top Secret security clearance. Preferred Qualifications · Experience with thermal analysis tools such as STAR-CCM+, ANSYS, Icepak, Flotherm, or comparable FEA / CFD platforms. · Experience using MATLAB, Python, spreadsheets, or similar tools for first-order thermal modeling, transient analysis, or engineering trade studies. · Experience designing thermal hardware such as heat sinks, cold plates, fans, pumps, heat exchangers, thermal interface materials, liquid cooling systems, or air-cooling systems. · Experience planning or executing thermal tests, including sensor selection, data acquisition, data post-processing, and correlation of test results to analysis. · Experience with SolidWorks, Siemens NX, or comparable CAD tools. · Experience supporting formal design reviews, customer reviews, flight test, qualification testing, or fielded hardware. · Experience developing reusable analysis tools, automation workflows, reduced-order models, or other methods that improve analysis speed and consistency. · Strong motivation to support Client’s mission of defending the United States and allied partners.

Location: Costa Mesa, United States 📍 Location: Costa Mesa, California 📄 Employment Type: Contract-to-Perm 🏢 Work Arrangement: Remote Opportunity for Top Candidates 🚀 Start Date: TBD 💰 Compensation: TBD — based on skills and experience Important Screening Requirements Remote opportunity is open to qualified candidates within the United States . Relocation assistance is available to qualified candidates from other countries. 5+ years of experience designing, analyzing, or validating thermal systems for integrated hardware products. MS or PhD in Mechanical Engineering, Aerospace Engineering, Applied Physics, or a related field, with a focus on heat transfer, fluid dynamics, thermal sciences, or thermal systems. Strong first-principles understanding of heat transfer and fluid dynamics . Experience supporting thermal design for aerospace, aircraft, rocket, missile, UAV, defense, or other high-performance hardware . Experience with thermal analysis, modeling, simulation, and/or physical test data. Ability to communicate technical tradeoffs across engineering, program, and customer stakeholders. Ability to obtain and maintain a U.S. Top Secret security clearance , where required. About the Role We are seeking a Senior Thermal Engineer to own thermal design and analysis for advanced defense hardware across drones, aircraft, missiles, and related flight systems. This role is ideal for an engineer with deep expertise in heat transfer and fluid dynamics , strong thermal analysis capabilities, and the engineering judgment to select the appropriate level of analysis—from first-order hand calculations through detailed FEA and CFD—to support rapid and effective design decisions. You will work across multidisciplinary engineering teams to develop thermal architectures, evaluate system performance, support prototype testing, and drive thermal design decisions for demanding operating environments. What We’re Looking For We’re looking for a senior thermal engineer who can take ownership of thermal engineering from early design and analysis through testing and validation . The ideal candidate combines strong fundamentals in heat transfer and fluid dynamics with hands-on experience applying thermal analysis to complex, high-performance hardware. You should be comfortable working across disciplines, making engineering tradeoffs, troubleshooting thermal issues, and communicating technical recommendations to both engineering and customer stakeholders. Key Responsibilities Thermal Design & Analysis Own thermal design and analysis for integrated hardware products, including drones, aircraft, missiles, and related defense systems . Apply first-principles engineering judgment to determine the appropriate level of analysis for each design decision, including: Hand calculations Spreadsheets MATLAB/Python models FEA CFD Define thermal architectures capable of operating in rugged environments and demanding flight envelopes. Evaluate hot, cold, transient, and mission-specific thermal conditions . Cross-Functional Engineering Partner with electrical, mechanical, aerospace, software, and systems engineers to document: Power dissipation Operating modes Thermal constraints Design tradeoffs Build and maintain thermal FEA/CFD models to predict system performance, establish design limits, and define red/yellow operating thresholds for testing and field use. Prototype Testing & Validation Define and execute prototype builds and thermal tests. Support CAD activities, sensor selection, DAQ setup , data post-processing, and test-result documentation. Use test data and thermal analysis to validate designs and support engineering decisions. Technical Leadership & Continuous Improvement Present thermal status, risks, tradeoffs, timelines, and recommendations during internal design reviews and customer-facing technical reviews. Develop internal tools, workflows, and analysis methods that improve the speed, consistency, and quality of thermal decision-making. Support failure reviews and root-cause investigations using test data, thermal analysis, and first-principles engineering reasoning. Required Qualifications MS or PhD in Mechanical Engineering, Aerospace Engineering, Applied Physics, or a related field focused on heat transfer, fluid dynamics, thermal sciences, or thermal systems. 5+ years of experience designing, analyzing, or validating thermal systems for integrated hardware products. Strong first-principles understanding of: Conduction Convection Radiation Fluid flow Transient thermal behavior Experience supporting thermal design for aerospace, aircraft, rocket, missile, UAV, defense, or other high-performance hardware systems. Experience using thermal analysis, modeling, simulation, and/or physical test data to drive design decisions for passive or active thermal management systems. Ability to clearly communicate technical tradeoffs across engineering, program, and customer stakeholders. Ability to obtain and maintain a U.S. Top Secret security clearance , where required. Preferred Qualifications Experience with thermal analysis tools such as: STAR-CCM+ ANSYS Icepak FloTHERM Comparable FEA/CFD platforms Experience using MATLAB, Python, spreadsheets , or similar tools for first-order thermal modeling, transient analysis, or engineering trade studies. Experience designing thermal hardware such as: Heat sinks Cold plates Fans Pumps Heat exchangers Thermal interface materials Liquid cooling systems Air-cooling systems Experience planning or executing thermal tests, including sensor selection, data acquisition, data post-processing, and correlation of test results to analysis. Experience with SolidWorks, Siemens NX, or comparable CAD tools . Experience supporting formal design reviews, customer reviews, flight testing, qualification testing, or fielded hardware. Experience developing reusable analysis tools, automation workflows, reduced-order models, or other methods that improve analysis speed and consistency.

Location: London, UK Workplace: Hybrid Sensor Tower’s digital intelligence platform provides unparalleled insight into market trends, advertising, competitor’s strategies, and consumer/user audience across mobile, web, and gaming. Sensor Tower’s insights are trusted by more than 2,500 enterprises worldwide across tech, retail/commerce, entertainment/media, gaming, consumer packaged goods and finance. Role Summary: As a Customer Support Specialist, you’ll be on the front lines of customer interaction, playing a vital role in delivering exceptional service and resolving inquiries efficiently and empathetically. In this role, you will gain hands-on experience within the fast paced, ever evolving mobile app ecosystem and have the opportunity to engage directly with executives and team members from high growth companies. You’ll also collaborate across departments, working closely with product, engineering, and operations teams to ensure a seamless customer experience and to provide feedback that helps shape the future of our platform. Fluency in French (written and spoken) to effectively support French-speaking clients and partners. Full time / London - Hybrid (2-3 days in office) - French Speaking Responsibilities: - Provide expert support to customers and the internal sales team by responding to queries in a timely and accurate manner. - Troubleshoot and resolve issues by gathering technical details, replicating problems, and using internal tools to identify root causes. - Collaborate with cross functional teams to escalate complex issues, log bugs, and clearly communicate technical solutions to users of varying technical backgrounds. - Provide high priority support and platform overviews on an ad hoc basis to a designated group of strategic accounts. - Act as a bridge between internal teams, sharing relevant customer feedback to improve the platform. - Identify gaps in resources based on common customer pain points. - Educate users on new updates, tools, and best practices to tailor to their use cases - Report on key customer service metrics and identify noteworthy trends to the Team Director. Qualifications: - At least 4-5 years of experience in a data analysis customer facing role (customer service, care, or success). - Fluency in French/English - Background in mobile analytics, consumer behavior, or digital advertising strongly preferred. - Passionate about providing exceptional customer experience. - Strong attention to detail and ability to manage multiple tickets or issues at once. - Comfortable working with and supporting global brands across diverse markets. - Genuine interest in building and growing a career within customer support. - Technical experience in initial troubleshooting of front end bug/network issues. - Ability to read and interpret data visualizations or logs to guide troubleshooting. - Experience working cross functionally with Product, Engineering, or Data teams. - Proactive in spotting recurring issues and patterns in customer inquiries. Nice to have: - Hands-on experience with platforms such as Zendesk, Mailgun, Kibana, and Salesforce. - Knowledge in assisting global users with API questions, data import/export execution, and platform integrations. Fraud warning: It's common for scammers to create positions that look legitimate on other sites. To ensure your submission is considered, only apply for positions at Sensor Tower through our company website or through posts directly associated with Sensor Tower company profiles on sites such as LinkedIn, Indeed, BuiltIn or Hackajob. At no point will Sensor Tower ever ask for money, credit card, or bank account information to complete a job application. Communications received from Sensor Tower are only sent by e-mail addresses ending in sensortower.com http://sensortower.com. All Sensor Tower interviews will be conducted via phone or Zoom. At no time will a conversation be moved to an alternative email outside of sensortower.com http://sensortower.com or text. Should an issue arise that you feel we should be aware of, please contact us. Please provide your resume when applying. To all recruitment agencies: Sensor Tower does not accept third party resumes. Please do not send resumes to our jobs alias, Sensor Tower employees or any other organization location. Sensor Tower is not responsible for any fees related to unsolicited resumes. Sensor Tower will not pay any third-party agency or company that does not have a signed agreement with Sensor Tower. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. We're looking for a Senior/Staff Product Engineer to join our Embodied AI team. Working alongside the group's GM, Product leader, and robot learning engineer, you'll own how the product reaches customers, build the integrations that make it native to their simulators and deployment stacks, and influence the roadmap. You've turned capabilities into products. You've shipped developer-facing products and watched adoption turn on details nobody planned for. You know that a capability isn't a product until someone outside the building has used it without help, and you're passionate about the work that sits between the two. This is not a role for someone who wants to manage and not ship, or someone who wants to ship without ownership of commercial consequences. This is a role for an entrepreneurial engineer who loves to build and is energized by making the people around them, researchers and customers alike, more effective. You have a co-founder mentality. You may have been part of a founding team before, or want to start your own business one day. What You'll Do - Build the Product Surface - Own how autonomy teams experience our work: the APIs, UIs, packages, and documentation. - Make Our World Native to the Customer's - Turn scans and reconstructions into reliable, interoperable assets that work in customers' simulation tools and workflows, including packaging, metadata, semantic labels, object structure, and selectable variants. - Turn Prototypes Into Capability - Partner with reconstruction, mapping, localization, and research teams to transform prototypes and pipeline outputs into production-grade services and user experiences. - Deliver at Scale - Design and operate backend systems for accounts, organizations, sites, scans, assets, processing jobs, permissions, asynchronous workflows, storage, and data access. - Make It Work - Work directly with customers and internal users to integrate our technology, diagnose failures, improve reliability, and close the gap between intended and actual product behavior. - Influence the Roadmap - Work alongside the group's GM, Product leader, and robot learning engineer to shape what we build and when. What You'll Bring - 6+ years of software engineering experience; Bachelor's degree in Computer Science or a related field, or equivalent practical experience. - Significant experience building and operating production web applications and backend services, with strong fundamentals in API design, data modeling, testing, observability, and reliability. - Shipped developer-facing products — including the documentation and reference code external engineers actually used — and worked with 3D asset formats or comparable binary formats to production depth: you can say what the conventions were, where they broke, and what it cost you. - Proficient in Python and TypeScript, comfortable working across frontend and backend, and able to take a feature from product requirements through to running it in production. - Experience designing asynchronous workflows, long-running jobs, external integrations, and data-intensive systems. Nice to Have - Experience working with robotics simulators or toolchains such as Isaac Sim, Isaac Lab, or MuJoCo, or OpenUSD. - Built products for geospatial, 3D, computer vision, graphics, robotics, or spatial computing. - Worked on visualization or asset-management experiences with React, Next.js, or Three.js. Competencies - Relentless bias for action. You make decisions and ship as if the company’s success depends on it, because it does. You set the pace, and drive the people around you to rise to it. - Intellectually honest. You know there’s just one job that underpins every other in a startup: find the truth. You are relentless in your pursuit of it, including when it challenges your own convictions, and you raise concerns when you see them — even when it's uncomfortable, and especially when it's unpopular. - Pragmatic. You have no patience for not-invented-here syndrome and analysis paralysis. You find the fastest path to a working capability without one-way doors that undermine scaling. - Confident and credible with customers. You can read an autonomy engineer's training config, find why our asset didn't load, and explain the fix in their terms. - Fluent in other people's ecosystems. You'll spend much of your time learning new tools and stacks. You're quick to learn the customer's language, and you can point to something you shipped in a world that was foreign to you a quarter earlier. Compensation & Benefits The base salary range for this role is $207,000 - $265,000, and your offer within it will reflect your experience and the scope you take on. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Real-World Test Lab (RWTL) Physical AI doesn't get graded on a leaderboard. It gets graded on a factory floor at shift change, in a substation with no GPS, on a site where the lighting is wrong and the stakes are real. The Real-World Test Lab closes the gap between the benchmark and the field. We bring the customer's world inside our walls — their devices, their environments, their hardest conditions, and their definition of success — and make it the bar every release has to clear. As Niantic Spatial's first and most demanding customer, we push our reconstruction, localization, and spatial understanding to their limits, find where they shine and where they break, and turn that into evidence that shapes what we build next. It's a new team at the frontier of physical AI, and you'll help invent how the job is done. About the Role We're hiring a Hardware Operations Engineer with a robotics specialism, reporting to the Director of the Real-World Test Lab, to own the physical layer of our evidence. You'll manage our fleet of capture devices and robots, engineer the test environments and the instrumentation inside them, support the captures our data programs depend on, and run physical test sessions, including the real-robot side of our sim-to-real work. A physical run only counts as evidence if the hardware is characterized, the environment is controlled, the ground truth is trustworthy, and someone can reproduce the run months later. You'll build what makes that possible: fixtures, ground-truth references, calibration and data-offload tooling, and the integrations that feed physical runs into the same automated evaluation system as everything else. You engineer the conditions, not just the setup. When a physical result didn't match expectations, you've worked out whether the hardware, calibration, environment, or system under test was responsible. Then you built the rig, reference, or logging that kept the question from coming back. You know an uninstrumented physical test is an anecdote, and in the Lab you'll be the person who can say with authority whether a strange result is real. What Success Looks Like - 30 days: Fleet inventory and characterization baseline complete, safe operating procedures defined for current spaces, and first instrumentation gaps identified. - 60 days: First physical robot run executed with ground-truth instrumentation, documented well enough to repeat, with results in the Lab's evaluation system. - 90 days: Test environments in regular use with controlled, documented conditions; capture support running smoothly with our data acquisition team; and the physical side of sim-to-real running on a standing instrumented protocol. What You'll Do - Own and Characterize the Fleet - Manage our capture devices, sensors, and robots end to end: inventory, calibration, firmware, maintenance, logistics, and spares. Characterize what each platform can and cannot do, so a device's limits are a known quantity rather than a surprise inside a result. - Engineer the Physical Test Environments - Design, build, and operate the spaces we test in, covering layout, lighting control, markers, obstacle configurations, and survey-grade ground truth references, across our office, rented or workplace-services-supported space, and partner or customer sites. Make each environment a controlled variable rather than an improvisation. - Build the Instrumentation - Create the rigs, mounts, references, and measurement setups that turn a physical run into quantitative data: trajectory ground truth, positional accuracy references, timing and synchronization across sensors, and automated condition logging. - Integrate Physical Runs Into the Evaluation System - Work with the AI Automation Engineer so physical results flow into the same scorecards and comparisons as software-only evaluations, through automated data offload, run metadata, and structured condition capture rather than a spreadsheet and a folder of files. - Run the Physical Test Sessions - Execute robot runs and device-in-the-loop tests: robot bring-up, teleoperation, scripted trials, and the repetition that makes a result statistically meaningful rather than anecdotal. - Own the Physical Half of Sim-to-Real - When a scenario has been evaluated in simulation, engineer and execute its physical counterpart so the comparison is valid, matching environment, route, lighting, sensor configuration, and robot setup, and instrumenting the run so divergence is explainable rather than mysterious. - Own Safety - Define and maintain safe operating procedures for robots and powered equipment in our test spaces, and coordinate with workplace services, IT, Legal, and site owners on access and safety requirements. - Automate Your Own Work - Script the repetitive parts, including configuration, calibration checks, data offload, and condition logging, so setup time falls and a colleague can run a session without you. What You'll Bring - Hands-on engineering experience with robotic hardware, covering bring-up, integration, teleoperation, troubleshooting, and maintenance. Mobile or wheeled platforms preferred. - Built test rigs, fixtures, or instrumentation that produced quantitative measurements of a physical system's behavior. - Designed and run structured physical experiments, including ground truth methodology, and documented conditions rigorously enough for someone else to reproduce them. - Worked with sensor calibration, multi-sensor synchronization, and coordinate frame conventions, and understand how errors in each propagate into a result. - Strong Python and command-line proficiency, with a track record of automating hardware configuration, data offload, or test execution. - Managed hardware fleets operationally: inventory, firmware, calibration schedules, logistics, and repair coordination. - Practical safety experience operating powered equipment or robots around people. - A bachelor's degree in a relevant field, or equivalent experience. Nice to Have - Worked with ROS or ROS 2, including writing nodes or integrating sensor drivers. - Operated NVIDIA Isaac Sim or Isaac Lab as a user, running scenarios someone else authored. - Worked with professional capture hardware such as terrestrial laser scanners, NavVis or Leica systems, LiDAR, 360 cameras, or drones. - Established survey-grade or motion-capture ground truth for localization or navigation evaluation. - Supported photogrammetry, Gaussian splat, or 3D reconstruction capture workflows. - Run test operations at customer or partner sites, with the coordination and discretion that requires. Competencies - Engineering judgment about physical systems. You reason about error sources: calibration drift, timing offsets, mounting rigidity, lighting variation, floor surface. When results disagree, you form a hypothesis and design the measurement that settles it. - Hands-on and unfazed. You'd rather be in the space with the robot than reading about it. Cables, mounts, batteries, firmware, and a session that starts at 7am are all part of the job. - Meticulous about conditions. You instrument rather than remember. You know the value of a physical test lives in how precisely its conditions were captured. - Safety-minded without being slow. You take real responsibility for operating robots around people, and you build procedures where the safe path is also the fast path. - Builds for other people. Your fixtures, scripts, and procedures get used by colleagues without you in the room. - Comfortable in an unfinished environment. Much of this does not exist yet. You'll be selecting equipment, designing the first rigs, and defining how a space gets configured, with support but without a playbook. Compensation & Benefits Base salary range of $142,200 to $193,000. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Real-World Test Lab Physical AI doesn't get graded on a leaderboard. It gets graded on a factory floor at shift change, in a substation with no GPS, on a site where the lighting is wrong and the stakes are real. The Real-World Test Lab closes the gap between the benchmark and the field. We bring the customer's world inside our walls - their devices, their environments, their hardest conditions, and their definition of success - and make it the bar every release has to clear. As Niantic Spatial's first and most demanding customer, we push our reconstruction, localization, and spatial understanding to their limits, find where they shine and where they break, and turn that into evidence that shapes what we build next. It's a new team at the frontier of physical AI, and you'll help invent how the job is done. About the Role We're hiring an AI Automation Engineer, reporting to the Director of the Real-World Test Lab, to build the system that produces our evidence. Today our evaluations are manual, inconsistent, and slow. You'll design and own the automation that runs them end to end on every relevant release, with no human driving it, turning one-off experiments into an always-on service the whole company relies on. This role is about owning the evidence, not executing a test plan. You'll decide how each workflow gets exercised, and you'll be measured on whether the company can trust the results, not on how much automation exists. The work counts when it keeps running correctly months later, without you in the loop. You believe evaluation is engineering, not process. You've built systems that test other systems, and you know the difference between a script that works on your laptop and infrastructure a team can trust. When a result couldn't be reproduced, you fixed the tooling instead of arguing about the number. What You'll Do - Build the Evaluation Machine - Own the automation that executes Lab evaluations end to end: environment setup, run orchestration, artifact capture, and result collection. Make reruns free so we test constantly rather than occasionally. - Make Results Comparable - Instrument scorecards so a result can be compared across product versions, devices, and capture conditions. A number without its lineage is not evidence. - Automate the Agent-Driven Layer - Build the agent workflows that exercise priority customer use cases at realistic scale, across the graded difficulty spectrum from easy to frontier, and be honest about where agents cannot yet replace human judgment. - Kill Manual Work Permanently - Convert one-off experiments into standing protocols that run on every relevant release. Automate recurring inspection wherever it can be automated, and route what genuinely cannot to scalable human review. - Make Failures Actionable - Produce diagnostics precise enough that a finding reaches its owner with a reproducible case and data attached. Findings that need re-investigation before anyone can act on them are half-finished. - Keep Data From Being the Bottleneck - Work with the AI Data Manager so every run is reproducible from a known dataset state, without anyone downloading and re-uploading data by hand. What Success Looks Like - 30 days: One priority workflow evaluated end to end with no manual steps, with results in a comparable scorecard. - 60 days: Evaluations trigger automatically on relevant releases, with diagnostics that route failures to the right owners. - 90 days: Three priority workflows under standing automated evaluation, with version-over-version comparison for leadership. What You'll Bring - Built and maintained production-grade automation or test infrastructure that other engineers relied on daily. - Experience evaluating systems where correctness is graded rather than binary, meaning quality, accuracy, or latency thresholds rather than pass/fail assertions. - Strong Python, with fluency in orchestration, CI-style pipelines, cloud storage, and reproducible environments. - Worked with backend services and APIs you did not own, integrating against them without becoming a bottleneck for their team. - Written up a technical finding clearly enough that a non-author could act on it without a meeting. - A bachelor's degree in a relevant field, or equivalent experience. Nice to Have - Built agent-based or LLM-driven automation for a task that previously required human judgment. - Worked on evaluation or benchmarking for computer vision, 3D reconstruction, or spatial systems. - Instrumented dashboards or scorecards that leadership used for release decisions. - Operated data provisioning or registry infrastructure across multiple environments and access models. Competencies - Intellectually honest. You design tests that produce answers people can trust, and you refuse to let a benchmark imply more than the evidence supports — including when the honest answer is inconvenient for your own work. - Pragmatic. You find the fastest path to a defensible result without going through one-way doors that undermine scaling. You have no patience for building infrastructure nobody has asked for yet. - AI-forward by instinct. You reach for agents and LLM-driven automation before you reach for headcount, and you're rigorous about verifying what they produce. - Builds for other people. You've maintained something after the initial excitement wore off. Your tooling is documented, your failures are legible, and colleagues use what you build without asking you to run it for them. Compensation & Benefits Base salary range of $158,400 to $210,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. WHOOP is hiring a Staff Hardware Test Engineer (Manufacturing) to lead manufacturing test strategy and deliver scalable test solutions that ensure every WHOOP device meets the highest standards of quality and reliability. You will take ownership of complex manufacturing test challenges from high-level objectives through strategy, execution, and production outcomes. Working across Manufacturing Engineering, Electrical Engineering, Firmware, Mechanical Engineering, Quality, and Reliability, you will drive alignment on test strategy, influence product and manufacturing decisions, and deliver measurable improvements in test coverage, quality, yield, cycle time, and cost. You will also establish best practices, raise engineering standards, and mentor engineers across the team.   RESPONSIBILITIES: - Lead the architecture, development, validation, and deployment of automated test equipment (ATE), electrical test fixtures, and control systems for engineering validation, NPI, and mass production. - Develop and establish scalable automated test methodologies and applications using Python to validate electrical, functional, RF, and sensor performance on manufacturing lines. - Drive cross-functional alignment across Hardware, Firmware, Manufacturing, and Quality engineering teams to make tradeoffs around test coverage, product quality, cycle time, yield, cost, and schedule. - Lead complex and ambiguous manufacturing test investigations, structuring problems, identifying technical and operational risks, and driving cross-functional teams to root cause and resolution. - Own manufacturing test readiness and outcomes through factory bring-up and production ramp with manufacturing partners, including fixture qualification, calibration, correlation, troubleshooting, and continuous improvement. - Analyze manufacturing and test data to identify systemic opportunities and deliver measurable improvements in yield, process capability, test coverage, quality, cycle time, and cost. - Establish manufacturing test best practices, methodologies, and standards that improve execution quality and scalability across programs. - Identify technical and execution risks proactively and drive mitigation strategies with engineering teams and manufacturing partners. - Contribute to product and manufacturing roadmaps by identifying test technology, infrastructure, and capability investments required for future products. - Mentor engineers and provide technical guidance on test architecture, debugging, automation, and manufacturing test methodologies. QUALIFICATIONS: - Bachelor's degree in Electrical Engineering, Computer Engineering, or a related technical discipline. - 10+ years of experience developing hardware test systems, automated test equipment, or manufacturing test solutions for high-volume consumer electronics or similarly complex products. - Demonstrated experience independently owning manufacturing test strategy and execution from product development through NPI, ramp, and mass production. - Proven ability to lead complex, ambiguous technical initiatives and drive outcomes across multidisciplinary engineering and operations teams. - Deep understanding of electronics, instrumentation, measurement systems, and communication protocols such as UART, I²C, SPI, USB, Bluetooth, and NFC. - Experience designing electronic circuits and PCBAs using tools such as Altium Designer. - Strong proficiency in Python for developing automated manufacturing test applications; experience with C/C++ or other systems languages is a plus. - Extensive experience designing, validating, and debugging manufacturing test fixtures, instrumentation, and production hardware. - Strong understanding of manufacturing test methodologies and data analysis, including test coverage, calibration, correlation, GR&R, process capability, yield analysis, and failure analysis. - Extensive experience working with CMs and JDMs, including factory bring-up, NPI, production ramp, and sustaining support. - Demonstrated ability to influence technical decisions, align stakeholders, and communicate effectively across engineering, operations, and leadership. - Track record of delivering measurable improvements in manufacturing quality, yield, efficiency, test coverage, or cost. - Experience mentoring engineers and improving engineering practices within a team. - Ability to travel up to 15%, both domestically and internationally. - Strong commitment to leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $180,000.00 - $215,000.00 Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements. Learn more about WHOOP https://www.whoop.com/us/en/careers/?srsltid=AfmBOopKmph9d0DLBlogZu8mx6do0dzjNS8eJlfc4PQqQtdU6F8DGKBg.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Data Center Security Engineering (DCSE) owns physical security across Anthropic's data center footprint: the sites, the hardware inside them, and the supply chain that delivers it. The Security Fusion Platform is where physical security signals from across that footprint are correlated and put in front of the analysts who act on them. It carries continuous monitoring, audit evidence, metrics, and analyst response, along with the classification and analytics pipelines that turn sensor data into events. You'll build and own the platform analysts work from. This is a foundational role. You'll build the software platform that carries a signal from source to analyst decision, ship its first versions, and keep them running in production. The sensors and systems at each site belong to other DCSE engineers; you define the event contract their owners deliver to, and you build the classification and analytics pipelines that run over what those sources produce. Physical security systems engineers own the operations spaces; you own the software that runs in them. You'll work alongside engineers focused on the sites themselves. What you lead, you own end to end: the design, the technical approach, and the result in production. You'll work with external vendors and integrators, setting requirements and acceptance criteria for what you own and deciding what the team builds itself. We use Claude throughout our engineering workflow and expect you to as well. This role involves regular travel to data center sites. No security clearance is required. These are critical services, and you'll take part in on-call for them. Key responsibilities Design and build the event bus and normalized event schema: source identity, sequencing, health state, and the adapter contract that owners of each sensor and system feed build to, plus adapters where needed Build correlation and alerting: the rules and services that turn events from independent sources into alerts an analyst can act on Build the classification and analytics pipelines: computer vision and multi-sensor fusion, with results landing on the event bus Build analyst surfaces: the queue, escalation tooling, dashboards, camera viewers, and video wall content a 24/7 watch works from, plus video analytics integration so camera streams arrive on the bus as events Deliver audit evidence: durable, tamper-evident event history, evidence exports, and the retention and access controls around them Instrument metrics and self-monitoring: detection rates, nuisance ratios, alert aging, time to resolve; heartbeats and loss-of-telemetry alarms on every feed, tested fail-secure behavior, and change audit on every rule Deploy across sites: site-local components, central services, and the sync that keeps configuration, rules, and state consistent, then commission each site and hand over to the analysts Specify the compute the platform runs on (servers, storage, and the platform's network segment) to the team's segmentation and hardening baseline Write requirements and acceptance criteria for what vendors and integrators deliver, review deliverables against them, and make the call on accepting or rejecting the work Minimum qualifications Have built and run event-driven backend systems in production Are proficient in at least one backend language such as Python, Go, or Rust, and have worked with a message bus or event streaming system such as Kafka Have owned a system end to end: set the design, made the tradeoffs, shipped it, and answered for it in production Have integrated with external systems you did not control (vendor APIs, on-prem appliances, video platforms, building systems) and designed for a life beyond any one vendor Have directed vendor or integrator work: written requirements and acceptance criteria, reviewed deliverables against them, and decided what gets accepted Design for the failure you won't see coming (a silent feed, a lost network path, a replayed event, a de-tuned rule), know how your system behaves when a source lies or goes quiet, and test for it Build tools for people who use them under pressure and iterate with those operators Preferred qualifications Experience building or operating a security operations platform (SOC, physical security operations, or the detection engineering behind one) Experience building ML or computer vision inference pipelines over video and sensor streams PSIM (physical security information management) or VMS (video management system) integration experience, or familiarity with physical access control and building systems data Experience producing evidence for auditors or assessors: log integrity, retention, chain of custody Experience using AI-assisted development tooling as a core part of your workflow The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. WHOOP is seeking a CAD Sculptor, Industrial Design, Lead to translate design intent into refined, manufacturable 3D data across our ecosystem of wearables, bands, accessories, charging systems, and packaging. Sitting at the intersection of industrial design, engineering, prototyping, and manufacturing, you will create production-ready surface models that preserve the nuance of design intent while meeting functional, ergonomic, and manufacturing requirements. You will bring exceptional form sensitivity, advanced surfacing expertise, and strong cross-functional judgment to help move beautiful, high-performance products from early concept through production. RESPONSIBILITIES: - Partner closely with industrial designers to translate sketches, physical models, scan data, reference CAD, and design direction into precise, refined digital models that capture intended form, proportion, and product character. - Create advanced NURBS surface models in Autodesk Alias with strong attention to curvature, continuity, highlight control, transitions, draft, and overall surface integrity for concept development, prototyping, engineering review, and production handoff. - Bridge Alias and parametric CAD workflows, including SolidWorks, to ensure sculpted design surfaces integrate effectively with mechanical assemblies, engineering requirements, manufacturing constraints, and production-intent models. - Support product development from early form exploration and ergonomic studies through prototype refinement, DFM, tooling development, production release, and manufacturing ramp while preserving design intent. - Collaborate with Industrial Design, Mechanical Engineering, Hardware, Manufacturing, Apparel, CMF, and Product teams to resolve challenges related to wearability, fit, construction, sensor integration, charging interfaces, assembly strategy, durability, and manufacturability. - Elevate digital modeling practices across the Industrial Design organization by contributing strong craftsmanship, mentoring where appropriate, and improving surfacing standards, model organization, data exchange, design-to-engineering handoffs, and emerging AI-assisted design workflows. QUALIFICATIONS: - 6+ years of experience in CAD sculpting, industrial design modeling, advanced surfacing, or a related 3D product development discipline, with experience supporting products through production. - Expert proficiency in Autodesk Alias or a comparable advanced surfacing platform, with demonstrated mastery of NURBS surfacing, curve quality, surface continuity, highlight control, transitions, and production-aware model construction. - Strong proficiency in parametric CAD, preferably SolidWorks, with the ability to build, modify, reference, and collaborate effectively within engineering-oriented CAD models and assemblies. - Demonstrated experience developing consumer products, ideally including consumer electronics, wearables, accessories, softgoods-integrated products, charging systems, or other products with complex ergonomic and mechanical requirements. - Strong understanding of industrial design principles and manufacturing considerations, including proportion, silhouette, detail resolution, part breaks, assembly interfaces, draft, tooling constraints, tolerances, materials, and high-volume production processes. - Proven ability to collaborate with industrial designers, mechanical engineers, manufacturing partners, and other cross-functional teams, clearly communicating modeling decisions, technical tradeoffs, risks, and opportunities. - A portfolio demonstrating exceptional 3D modeling craft, design sensitivity, advanced surfacing, parametric CAD integration, and meaningful contributions to production-intent or shipped products. - Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $100,000 - $150,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements. Learn more about WHOOP https://www.whoop.com/us/en/careers/?srsltid=AfmBOopKmph9d0DLBlogZu8mx6do0dzjNS8eJlfc4PQqQtdU6F8DGKBg.

Location: Riyadh, Saudi Arabia The Botanic Garden Maintenance Specialist is responsible for the specialised maintenance, environmental management, and plant-health care of botanic collections, with particular focus on rare, delicate, and environmentally sensitive species. The role ensures that greenhouses, conservatories, specialised plant areas, and associated horticultural systems maintain optimal growing conditions through systematic monitoring, preventative maintenance, and effective environmental control. Key Responsibilities Maintain optimal environmental conditions across greenhouses, conservatories, and specialised plant areas, including temperature, humidity, lighting, ventilation, and irrigation. Conduct regular plant-health inspections and identify signs of stress, pests, diseases, nutrient deficiencies, and environmental issues. Implement specialised care and maintenance protocols for rare, sensitive, and high-value plant collections. Operate, monitor, maintain, and troubleshoot irrigation, environmental control, lighting, sensors, and other horticultural systems. Manage irrigation and fertilisation programmes according to plant requirements, seasonal conditions, and water quality. Monitor soil, growing media, substrates, drainage, moisture, and root-zone conditions, and prepare or amend growing media as required. Implement greenhouse and conservatory cleaning, sanitation, sterilisation, and biosecurity procedures. Support Integrated Pest Management (IPM) and preventative plant-health programmes. Qualifications Bachelor's degree in Horticulture, Botany, Plant Sciences, or a related discipline. Specialist certification or training in greenhouse management, controlled-environment horticulture, irrigation, plant health, or horticultural equipment maintenance is advantageous. Fluency in English and Arabic is required. Experience Minimum 5 years of relevant professional experience in botanic garden maintenance, greenhouse operations, conservatories, specialist horticulture, or a comparable environment. Proven experience caring for rare, delicate, sensitive, or high-value plant collections. Hands-on experience with controlled-environment systems, irrigation, fertilisation, growing media, plant-health management, IPM, and greenhouse hygiene. Experience operating, troubleshooting, maintaining, and calibrating horticultural and environmental monitoring equipment. Experience implementing preventative and seasonal maintenance programmes and maintaining detailed technical and plant-health records. Experience working collaboratively with horticulture, facilities, engineering, contractors, and specialist technical teams. Previous experience in a botanic garden, conservatory, major public garden, research facility, or specialist horticulture environment is preferred. Core Competencies Specialist knowledge of botanic garden and controlled-environment horticulture. Strong plant-health assessment and diagnostic skills. Knowledge of irrigation, plant nutrition, soil and substrate management, IPM, and biosecurity. Strong technical and preventative-maintenance skills. Ability to interpret environmental monitoring data and respond to changing plant and system conditions. High attention to detail when working with sensitive collections. Strong planning, record-keeping, problem-solving, and organisational skills. Effective written and verbal communication and teamwork. Commitment to plant conservation, sustainability, safety, and horticultural excellence.

Location: London, UK Workplace: Hybrid Sensor Tower’s digital intelligence platform provides unparalleled insight into market trends, advertising, competitor’s strategies, and consumer/user audience across mobile, web, and gaming. Sensor Tower’s insights are trusted by more than 2,500 enterprises worldwide across tech, retail/commerce, entertainment/media, gaming, consumer packaged goods and finance. As an Account Manager, Brands at Sensor Tower, you’ll play a key role in managing the account renewal and growth of our customer base while working closely with Sensor Tower Customer Support as needed to ensure a positive customer experience. You’ll also be instrumental in helping to build our process around renewals management and advocate for process updates to improve operational efficiency. You will act as a trusted advisor to enterprise brand clients, ensuring they maximize the value of Sensor Tower’s market intelligence platform. By bridging commercial strategy with operational excellence, you will drive long-term retention, identify strategic expansion opportunities, and streamline our internal workflows. What you will do: - Manage a portfolio of businesses, focusing on renewals, upsells, and Net Revenue Retention (NRR) growth. - Oversee all assigned contract renewals to ensure timely and accurate execution - Accelerate the contract renewal process, mitigate identified risk, and ensure customer satisfaction - Own contract processes, including renewal CTA management, quote creation, maintenance of Salesforce opportunity records, sending of order forms, forecasting renewals outcomes, and tracking progress of signature - Work with Customer Support team (where needed) to identify at-risk accounts and put together a strategy to secure the renewal, as needed - Partner with Customer support and Sales Ops to communicate challenges in our current renewal process and advocate for improvements to increase our operational efficiency - Identify opportunities to expand Sensor Towers footprint within an account as part of the renewal process - Build strong relationships with customers through a regular cadence of calls, face-to-face meetings and on-site visits where possible. Use these conversations to understand their priorities, demonstrate value, address objections and identify renewal and expansion opportunities. - Build account plans that identify renewal risk, stakeholder changes, product adoption gaps and opportunities for expansion well ahead of contract expiry. - Lead commercial negotiations with customers and their procurement and legal teams, including pricing, contract structure and multi-year agreements. - Develop relationships with decision-makers across multiple teams and regions within each account. - Translate customer goals into relevant use cases across Sensor Tower’s products, and partner with internal specialists on demonstrations, insights and custom data requirements. - Maintain an accurate renewal and expansion forecast, with clear next steps and escalation plans for at risk accounts. - Hold regular commercial reviews with key stakeholders to understand budget plans, confirm renewal timelines and build support for continued investment. Experience and skills that you can bring: - Must be wiling to work from our London office three days a week. - Experience in SaaS sales as an Account Executive or Account Manager. - Strong understanding of the SaaS industry and digital ecosystem. - Ability to identify product penetration, renewal, and upsell opportunities within the managed customer base. - Ability to present complex data solutions in a clear and concise manner to a variety of audiences, including non-technical. - Self-starting attitude and entrepreneurial spirit highly encouraged! - An eye for detail following the industry trends and interpreting these into day-to-day business impact. - Enjoy working in small, fast-paced teams where you can take initiative and accountability and generate - results every day. - Experience managing complex SaaS renewals and expansions involving multiple stakeholders, products or regions. - Strong commercial judgement, including the ability to defend value, handle pricing objections and balance customer needs with revenue goals. - Confidence working with procurement and legal teams to move agreements through to signature. Fraud warning: It's common for scammers to create positions that look legitimate on other sites. To ensure your submission is considered, only apply for positions at Sensor Tower through our company website or through posts directly associated with Sensor Tower company profiles on sites such as LinkedIn, Indeed, BuiltIn or Hackajob. At no point will Sensor Tower ever ask for money, credit card, or bank account information to complete a job application. Communications received from Sensor Tower are only sent by e-mail addresses ending in sensortower.com http://sensortower.com. All Sensor Tower interviews will be conducted via phone or Zoom. At no time will a conversation be moved to an alternative email outside of sensortower.com http://sensortower.com or text. Should an issue arise that you feel we should be aware of, please contact us. Please provide your resume when applying. To all recruitment agencies: Sensor Tower does not accept third party resumes. Please do not send resumes to our jobs alias, Sensor Tower employees or any other organization location. Sensor Tower is not responsible for any fees related to unsolicited resumes. Sensor Tower will not pay any third-party agency or company that does not have a signed agreement with Sensor Tower. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Location: Singapore ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE JOB Mistral AI is seeking an Applied AI Engineer focused on robotics deployment. You will take state-of-the-art AI models and make them work on real robots, in real environments, for real customers. This is a hands-on role at the intersection of machine learning and physical systems: you will own the path from model to deployed autonomy, working alongside robotics engineers, ML researchers, and systems engineers to deliver end-to-end autonomous solutions across diverse use cases. WHAT YOU WILL DO - Integrate AI models with robotic hardware, sensors, and embedded systems, bringing modern perception and language-driven capabilities onto physical platforms. - Improve the robustness, reliability, and safety of robotic systems operating in real-world, unstructured environments. - Test and validate algorithms in simulation and in real-world deployments, moving fluidly between the two. - Analyze field data to improve model performance and system reliability, closing the loop between what happens on the robot and what happens in training. - Bring up, tune, and debug the autonomy stack — localization, mapping, navigation, and perception — on real hardware, from sensor calibration to real-time performance. - Develop and tune robot navigation behaviors — path planning, obstacle avoidance — so systems hold up in dynamic, cluttered, and partially observable environments. - Diagnose failures end-to-end: mapping drift, localization dropouts, perception edge cases, timing issues — and fix them. - Collaborate with robotics engineers, ML researchers, and systems engineers to deliver complete autonomous solutions for customer use cases, from prototype through production deployment. - Build and maintain the tooling needed for deployment, monitoring, and continuous improvement of deployed systems. ABOUT YOU - Bachelor's, Master's, or PhD in Mechatronics, Robotics, or a relevant discipline (e.g. Computer Science, Electrical or Mechanical Engineering). - Fluent in English with excellent communication skills. - Strong software engineering in Python and/or C++: clean, readable, high-performance code; comfortable working in and improving production codebases. - Knowledge of robotics frameworks such as ROS/ROS2. - Experience with robot perception and state estimation: SLAM, localization and mapping, path planning, sensor fusion, or computer vision. - Solid mathematical fundamentals — geometry, probability, and estimation — and the judgment to know when a hand-crafted algorithm beats a learned one. - Familiarity with simulation tools and robotics development environments (e.g. Isaac Sim, Gazebo, or similar). - Strong problem-solving skills and ability to work in interdisciplinary teams. - Comfortable with the messiness of the real world: hardware quirks, edge cases, and field surprises don't scare you. - Low-ego, collaborative, and eager to learn. - Doesn't need roadmaps. Ships. NICE TO HAVE - Experience deploying ML models on embedded or edge hardware (GPU/NPU inference, quantization, real-time constraints). - Hands-on experience with sensor modalities such as LiDAR, depth cameras, or IMUs, including calibration and time-synchronization. - Exposure to VLM/VLA models or other foundation-model approaches for robot perception and control. - Experience with navigation in GPS-denied or otherwise challenging environments, or with visual-inertial odometry. - Working knowledge of established autonomy tooling — e.g. Nav2, SLAM Toolbox, Cartographer, RTAB-Map, or AMCL — and knowing when to build versus reuse. - Experience with behavior trees, dynamic costmaps, or fleet-level navigation. - Contributions to open-source robotics or ML projects. - Experience with safety-critical or regulated deployment environments. - Track record of success through personal projects, professional projects, or academia. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. We're looking for a Senior Computer Vision Engineer to join our Embodied AI team, focused on 3D scene understanding and semantics. A reconstructed environment is only useful to a robot once it knows what is in it: which surfaces are floor, which objects can be grasped, moved, or opened, where one room ends and another begins. You'll work hand in hand with our Research Scientists to take advances in open-vocabulary perception, 3D semantic labeling, and scene graph construction and turn them into reliable capabilities that embodied AI teams can use in production. This is an applied research role. You'll live at the boundary between a research prototype and a production pipeline: adapting methods so they hold up on messy customer captures, lifting 2D semantic signals into geometrically consistent 3D, defining what "semantically correct" means for a downstream policy, and feeding what you learn back into the research agenda. You understand that the difficult part is often not the core method, but the messy inputs, edge cases, operational constraints, and downstream requirements surrounding it. You care about quality, cost, latency, and reliability, and you know that a system is only successful when people can depend on it. This is a hands-on engineering role for someone who wants to build, ship, and own outcomes. You'll help shape both the technology and the product, while remaining close to the code and the problems our customers are trying to solve. What You'll Do - Productionize 3D Scene Understanding Capabilities - Turn research prototypes in open-vocabulary segmentation, 3D semantic and instance labeling, affordance prediction, and scene graph construction into reliable pipeline components and services that operate across varied customer data and environments. - Own End-to-End Output Quality - Ensure that reconstructed environments carry labels, instances, and relationships that are consistent, complete, and correct enough for downstream simulation and policy learning, and define what "correct enough" means for each customer workflow. - Bridge Research and Production - Work day to day with the Embodied AI Research Scientist: pressure-test new methods on real customer data, identify where they break, and bring production and customer constraints back into research planning to prioritize the advances that matter most. - Make Systems Robust to the Real World - Diagnose failures caused by capture quality, scene complexity, scale, calibration, coordinate conventions, and other assumptions that prototypes often leave implicit. - Build Evaluation and Quality Infrastructure - Create datasets, regression tests, quality gates, and benchmarking tools that help the team measure whether changes improve the system. - Improve Performance, Throughput, and Cost - Profile and optimize GPU and distributed workloads, reduce unnecessary reruns, and help establish the economics of running reconstruction at scale. - Work Across the Product Boundary - Partner with Embodied AI product and engineering teams to understand customer requirements and deliver capabilities that fit real training, evaluation, and deployment workflows. Help evolve the representations, tooling, and operational systems that allow reconstructed environments to move reliably into customer applications. What You'll Bring - 5+ years of computer vision experience and a bachelor's degree or equivalent, - Significant experience building and operating production computer-vision, machine-learning, graphics, or data-processing systems. - Deep hands-on experience with scene understanding: semantic, instance, or panoptic segmentation; open-vocabulary detection and segmentation; or vision-language models applied to perception. - Experience taking 2D perception into 3D, such as multi-view label fusion, 3D semantic segmentation, instance tracking across views, or scene graph construction over reconstructed geometry. - Experience delivering reliable computer-vision or 3D systems used by other teams or customers, including the evaluation that proved they worked.. - Practical command of 3D and spatial data, including geometry, camera models, coordinate frames, calibration, and metric scale. - Strong Python and PyTorch skills, with the ability to work in C++ or other performance-oriented environments when needed. - Experience with cloud infrastructure, GPU workloads, distributed processing, or large-scale data pipelines. Nice to Have - Hands-on experience with 3D reconstruction, photogrammetry, structure from motion, Gaussian splatting, neural rendering, or meshing. - Experience with SLAM, visual positioning, localization, or large-scale mapping systems. - Experience with robotics, simulation, or embodied AI applications, in particular how semantic labels are consumed by a policy or a simulator. - Built evaluation or benchmarking infrastructure for perception or reconstruction systems. - Experience optimizing large-scale GPU inference workloads for cost, throughput, or latency. - A publication record or contributions to widely used open-source perception codebases. - Advanced degree in computer vision, robotics, machine learning, or a related field. Competencies - Relentless bias for action. You make decisions and ship as if the company’s success depends on it, because it does. You set the pace, and drive the people around you to rise to it. - Intellectually honest. You know there’s just one job that underpins every other in a startup: find the truth. You are relentless in your pursuit of it, including when it challenges your own convictions, and you raise concerns when you see them — even when it's uncomfortable, and especially when it's unpopular. - Pragmatic. You have no patience for not-invented-here Syndrome and analysis paralysis. You find the fastest path to a working capability without one-way doors that undermine scaling. - Strong systems instincts. You understand that production quality includes reliability, observability, cost, latency, maintainability, and usability—not just algorithmic accuracy. - Comfort with ambiguity. You can make progress when the problem, data, and requirements are still evolving. Compensation & Benefits Base salary range of $229,500 to $255,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: London Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. Niantic Spatial's R&D Team in London is seeking a Research Scientist to push the frontiers of Spatial AI, advancing our Large Geospatial Model as a dedicated member of the Embodied AI group. You will invent and develop algorithms and systems that sit at the cross-section of computer vision, machine learning, AI, graphics, and robotics. We're passionate about discovery, so we're looking for scientists who want to learn, publish, teach, and deploy every new invention. What You'll Do - Develop New Spatial Representations - Develop new spatial representations that embodied AI can learn from, train in, and act on. - Advance Real-to-Sim Pipelines - Advance real-to-sim pipelines connecting real-world observations, 3D reconstruction, simulation, and robotic policy learning. - Solve Emerging Spatial Problems - Solve emerging problems that relate to spatial intelligence, 3D scene representation, training data, model efficiency, and interactive systems. - Take Capabilities Through to Evidence - Take new capabilities through to evidence: what changed for the policy, not only what changed in the reconstruction. - Build Prototypes - Build proof of concept prototypes, initially for internal use, where some will need to run at production scale on customer data. - Collaborate Across Research and Product - Collaborate closely with researchers, engineers, and product partners to bring novel models to production. - Publish Your Work - Publish and present your work. What You'll Bring - A PhD in computer vision, robotics, graphics, machine learning, or a related field, or equivalent research experience, with a publication record at top venues. - Substantial expertise in robotics or embodied AI, including experience in sim-to-real transfer, domain randomization, policy evaluation, and simulation-based learning. - Deep experience with 3D scene representations: Gaussian splatting, neural fields, meshes, point clouds, or implicit representations. - You have applied generative or diffusion models to 3D data, such as scene completion, inpainting, relighting, or novel view synthesis from sparse capture. - You have worked on 3D semantics, open-vocabulary scene understanding, or scene graphs. - Proficiency in Python and Deep Learning libraries such as PyTorch. - GPU or graphics programming experience, such as custom CUDA kernels, shaders, or differentiable rendering. - A track record of contributing to widely used open-source research codebases. Nice to Have - Proficiency in C++. Compensation & Benefits Base salary range of £103,500 to £202,500. Compensation also includes an annual bonus, equity, and a comprehensive benefits package. Location & Work Model This role is based in our London office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

О направлении Роль отвечает за программную и управляющую часть автоматизированных систем UmproTech для американского рынка: robots, PLC/HMI, safety, sensors, industrial networks, alarms, recovery logic и remote diagnostics. Главная задача Если главный инженер определяет архитектуру системы, а механический инженер прорабатывает компоновку и механику, этот специалист заставляет всю систему правильно, безопасно и устойчиво работать. Основные обязанности 1. Программирование промышленных роботов. 2. PLC programming и HMI development. 3. Разработка sequence/state-machine logic. 4. Создание I/O architecture и machine interfaces. 5. Интеграция robots с laser, welding, conveyors, fixtures, vision и периферией. 6. Industrial networks, servo/motion, sensors и drives. 7. Safety PLC, light curtains, scanners, safety gates и interlocks. 8. Alarm, diagnostics и recovery logic. 9. Manual/automatic modes, recipes и fault handling. 10. Offline programming, simulation и cycle-time optimization. 11. Подготовка software к FAT и remote commissioning support. 12. Анализ логов и удалённая диагностика систем в США. 13. Создание reusable PLC/HMI/robot software libraries UmproTech. 14. Документирование программного обеспечения и commissioning procedures. Стандартизация Задача — не программировать каждый проект с нуля. Нужно создать единый UmproTech Automation software framework: структуру PLC, robot↔PLC communication, HMI, alarm codes, diagnostics, recovery, safety states и reusable function blocks. Пример задачи Есть роботизированная сварочная ячейка: robot, welding power source, fixtures, pneumatic clamps, safety scanner, gates, sensors, HMI и PLC. 1. Разработать control architecture и I/O list. 2. Сформировать sequence of operation. 3. Запрограммировать PLC, robot и HMI. 4. Реализовать safety states. 5. Создать alarm и recovery logic. 6. Реализовать ручной и автоматический режим. 7. Подготовить систему к FAT. 8. Подготовить инструкции для американского field engineer. Что выполняется из Москвы 1. PLC/HMI development. 2. Robot programming и offline simulation. 3. I/O, sequence, alarm/recovery logic. 4. Software documentation. 5. Анализ логов и remote troubleshooting. 6. Reusable software libraries и standards. Что выполняется в США 1. Физический монтаж и wiring. 2. Проверка реальных I/O и подключений. 3. Robot mastering и фактическая калибровка. 4. Финальная safety validation. 5. Commissioning, SAT и работа с клиентом. Требования 1. 4+ лет в промышленной автоматизации, PLC/АСУ ТП или industrial robotics. 2. Практический опыт программирования PLC и промышленного робота. 3. Опыт запуска реального промышленного оборудования. 4. Понимание IEC 61131-3, Structured Text, Ladder и Function Blocks. 5. Умение читать электрические схемы и работать с digital/analog I/O. 6. Industrial networks, servo/motion, sensors и machine safety. 7. Сильный troubleshooting и способность самостоятельно находить причину неисправности. 8. Структурированный код и техническая документация. 9. Английский для документации и переписки. Желательные платформы 1. PLC: Siemens, Beckhoff, Allen-Bradley, Codesys, Omron или Mitsubishi. 2. Robots: FANUC, ABB, KUKA, Yaskawa, Kawasaki, Universal Robots или аналогичные. 3. Практический commissioning ценится выше лабораторного опыта. Большое преимущество 1. Robotic welding, machine tending, laser automation. 2. Palletizing, material handling, conveyors. 3. Machine vision, grippers, pneumatics, servo systems. 4. Remote diagnostics, industrial data collection и OEE. Первые задачи 1. Выбрать совместно с главным инженером стандартную PLC architecture. 2. Создать robot↔PLC communication standard. 3. Разработать базовый UmproTech automation software framework. 4. Создать стандарт HMI, alarms, diagnostics и recovery logic. 5. Подготовить software первой robotic welding cell. 6. Участвовать в разработке automatic laser loading/unloading. Результат первых 12 месяцев 1. Рабочий UmproTech Automation software framework. 2. Первая запущенная robotic welding cell. 3. Первые customer projects в США. 4. Reusable PLC/robot function blocks. 5. Стандартизированные HMI, alarms, diagnostics и recovery procedures. 6. Сокращение времени разработки и commissioning следующих проектов. Отбор Кандидат получает практический кейс с robot, PLC, fixture, welding system, safety scanner и sensors. Нужно объяснить architecture, sequence, safety states, alarm/recovery logic и действия системы при сбоях. Главный критерий — способность построить устойчивую и обслуживаемую промышленную систему.

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role We're looking for an entrepreneurial Go-to-Market lead to build our pipeline and customer relationships within the Embodied AI group. One of the fundamental problems we’re helping the physical AI community overcome is the sim-to-real gap for visual-spatial understanding. We’re applying our team’s decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. Working directly alongside the group's General Manager, you'll map the market, open doors, and close business in step with product development. You'll have significant independence, direct access to the people building the product, and real responsibility for making the business successful. You're a natural-born seller. A day spent talking to customers gives you energy. You already know people in the robotics ecosystem, and you're always finding reasons to meet more. You earn attention, ask questions that teach us something, and turn interest into commitment. You're as good at listening as you are at making a case. When an opportunity matters, you are relentless, but your desire to win the right business is more powerful than your desire to win any business. This is not a role for someone who needs inbound leads, a finished playbook, or a fully baked product. You relish building. You take pride in finding the use case, earning the customer's conviction, and getting the deal over the line. The role will not initially carry a sales quota. It will carry clear accountability for qualified pipeline, useful customer learning, and business we can deliver. What You'll Do - Map the Market - Build and maintain a comprehensive view of prospects, their use cases, and the right contacts. Track funding, hiring, launches, and deployments, and hold a point of view on who we should pursue, why, and when. - Open Doors - Build qualified pipeline through your relationships, targeted outreach, introductions, and events. Get into the communities where our customers spend time, and turn the approaches that earn attention into repeatable ones. - Qualify and Learn - Get immersed in customers' workflows: what they're trying to do, what they've tried, where it breaks, and what that costs them. Establish fit, urgency, and how a buying decision will happen, and bring candid input on product-market alignment back to the General Manager and Product leader. - Develop Relationships - Be useful to accounts we're not ready to serve yet. Work with Marketing on insights, introductions, content, and events, and know what needs to change in their business or our capabilities for an opportunity to become actionable. - Close Business - Run opportunities through evaluation, proposal, negotiation, and signature. Agree what an evaluation must prove, who will decide, and what follows success. Prepare colleagues properly and stay engaged through handoff so commitments are delivered. - Shape the Commercial Model - Help design commercial models for a maturing product, finding simple solutions where the path isn't laid out, and bringing discipline to how early deals are structured. What You'll Bring - Relationships that open doors. You already know founders, engineering leaders, or buyers in robotics, embodied AI, or the infrastructure and tooling companies serving them, and you have a track record of building new relationships beyond your existing network. - Experience personally winning early customers for a technical product. You sourced opportunities and closed business while the use case, buyer, or commercial approach was still being worked out, and you can explain what you did to make it happen. - Experience shaping the deal itself. You've worked with founders or technical teams to turn a customer problem into a concrete offer covering scope, proof of value, commercial terms, and a path from evaluation to paid adoption, and you've secured commitments of budget and engineering time. - Evidence that you changed the approach because of what you learned. You can point to customer evidence that changed who your team targeted, what it offered, or how it sold, and explain what happened next. - Credibility with technical buyers. You've sold to engineering or research teams and can hold a substantive conversation about their workflows, including the roles of simulation, training data, and evaluation in embodied AI, and concepts such as reinforcement learning, imitation learning, and sim-to-real transfer. - A bachelor's degree in a relevant field, or equivalent experience. Nice to Have - You've turned initial pilots into sustained usage, renewals, or expansion. - You've helped turn a handful of early wins into a repeatable approach across customers. - You've partnered with or sold within the NVIDIA robotics ecosystem. - You've sold into defense or industrial robotics teams. Competencies - Painful sense of urgency. You move as if the company's success depends on it, because it does. People love working with you because you make things happen. - Strategically tenacious. You combine astute judgment about which opportunities matter with dogged determination to win them. When one door shuts on a great opportunity, you make sure another one opens. - Technically fluent. You speak the language of our customers, and know what the words mean. You get curious when a conversation gets technical, can explain our capabilities accurately, and recognize when a technical counterpart needs to take over. - Intellectually honest. You know there's one job that underpins every other in a startup: find the truth. You listen closely, ask about actual behavior, and investigate answers that don't add up. You don't mistake compliments for demand or keep a dead opportunity alive to make the pipeline look better. - Pragmatic in the face of ambiguity. You have a knack for finding simple solutions to complex problems when the path isn't laid out for you. You're not intimidated by designing commercial models or helping to mature a product. - Ability to close. You build champions, reach decision-makers, and methodically uncover what stands between interest and a purchase. You're a natural negotiator and enjoy delivering win-win outcomes. - Create value before you consume. You're generous with insights, thoughtful introductions, and practical help, always giving before asking for anything in return. When you ask for a customer's time or budget, you can explain what they stand to gain and hold us to delivering it. Compensation & Benefits Base salary range of $175,500 to $230,000. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.