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Location: Remote, Global ABOUT THE ROLE We are seeking a platform engineer to join our Compute team. This team owns the critical systems that power project provisioning, scaling, and the compute that our users rely on every day. You’ll work on the core platform that ensures Supabase can seamlessly scale across multiple regions, handle high-volume workloads, and provide low-latency, highly available compute services. You'll design, build, and operate systems that are both robust and highly automated — enabling us to provision new projects reliably at scale, optimize resource utilization, and deliver a seamless experience to the millions of databases which we manage. WHAT YOU’LL BE RESPONSIBLE FOR: - Help build and maintain the Supabase Cloud offering; - Design and implement systems to provision, scale, and manage the multi-region compute workloads powering Supabase projects; - Own the full lifecycle of compute orchestration: project creation, warm pools, autoscaling, resizing, and resource optimization; - Improve automation and observability across the compute stack to ensure high availability and performance; - Improve our system architecture to reduce costs while balancing security, reliability, and performance; - Collaborate cross-functionally with other teams to help leverage compute as a core platform offering; - Participate in on-call rotations, incident response, and post-incident reviews; - Resolve escalated support issues, while also identifying and resolving systemic issues across the platform. YOU MIGHT BE A GOOD FIT IF YOU: - Have strong software engineering skills (Go and Typescript required); - Experience building and operating cloud infrastructure or distributed systems at scale; - Have 5+ years experience with cloud infrastructure (AWS required, additional experience with GCP and Azure is a plus) - particularly compute, networking, and storage services; - Have 3+ years experience working with building custom Kubernetes controllers, and operating large-scale (tens-to-hundreds of thousands of pods) clusters; - Are knowledgable about networking and multi-region infrastructure design; - Are familiar with Postgres; - Have experience with Infrastructure as Code tools (Pulumi highly preferred, Terraform/CDK etc acceptable) - Have experience working with QEMU, KVM, and NAS is a plus; - Have experience with being part of on-call rotations for large production system; WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

In This Role, You'll Get to: Own and evolve the architecture of ACP: the orchestrator, per-host agent, and CLI that manage dedicated-resource virtual machines on bare metal, including compute placement, image management, and network recovery.

Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition). Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.

— Разрабатывать CV/ML-решения для преобразования чертежей в структурированные инженерные данные. — Работать с OCR, raster/vector geometry, CAD/BIM и пространственными связями.

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 Team Localization is where the map meets the moment. Our localization team builds the living geospatial world model and the centimeter-level Visual Positioning System (VPS) that lets people and robots know exactly where they are, from any camera, almost anywhere on Earth. That system is learned, not hand-built. Our localization stack has moved from classical geometry to visual models trained on billions of posed images — models that have to be accurate to the centimeter, robust to lighting and seasons and clutter, and fast enough to run in production for every query. This team sits at the junction of research and production: we take what works in a paper, make it work on our data, and make it work for customers. About the Role We're hiring an AI Engineer, Computer Vision, to contribute to the deep learning models at the heart of our localization system. Working alongside experienced researchers and engineers, you'll help train and iterate on the visual models — feature extractors, matchers, pose regressors, and retrieval models — that turn a single image into a precise position in the world. This is a full-loop environment. You'll get exposure to the entire pipeline: the data the model learns on, training, evaluation, and the service that runs it in production. You'll be surrounded by people who care deeply about correctness — where a loss curve going down is not the same as a system getting better — and you'll grow into that rigor quickly. What You'll Do - Train and Evaluate Models — Implement, train, and evaluate visual localization models in PyTorch: local feature extraction and matching, image retrieval, pose regression, and scene-coordinate regression. Iterate on architectures, loss functions, and training loops to improve accuracy on real production captures. - Build Data Pipelines — Contribute to high-throughput ingestion and preprocessing pipelines that turn raw imagery, poses, and 3D point clouds into training-ready datasets, including curation, sampling, and augmentation. - Run Experiments at Scale — Run training jobs across GPU environments on our 30-billion-image corpus, working with senior engineers and ML Infrastructure to keep experiments reproducible and results interpretable. - Extend the Benchmark — Help build and maintain the evaluation suite for localization — pose accuracy, recall across lighting and season changes, and latency under production load — so results are comparable across model versions. - Support Production Deployment — Work with senior engineers to take models from checkpoint toward serving: export, inference optimization, and monitoring once live. Learn what it means to own a model end-to-end, not just hand off a checkpoint. - Bridge Research and Product — Work with the Research team and Real-World Test Lab to understand how field failures translate into training data and benchmark improvements. What You'll Bring - Experience training deep learning models for computer vision tasks in PyTorch — through coursework, research, internships, or early industry work. - Foundational understanding of at least one of: visual localization, learned feature matching, image retrieval, pose estimation, SLAM, or structure-from-motion, and the 3D geometry underneath them (camera models, epipolar geometry, pose parameterizations). - Comfort working with large image or 3D datasets — preprocessing, curation, and understanding how data quality affects model behavior. - Familiarity with GPU-based training and the ability to read and reason about training runs — identifying whether a bottleneck is in data loading, compute, or model architecture. - Strong Python skills and a habit of writing code that others can rerun and build on. - A bachelor's or master's degree in computer science, computer vision, robotics, or a related field, or equivalent practical experience. Nice to Have - Published or contributed to work on learned localization, visual place recognition, scene-coordinate regression, or vision foundation models (CVPR, ECCV, ICCV, NeurIPS, 3DV, or equivalent). - Experience with large-scale self-supervised or multi-view pretraining, or fine-tuning vision foundation models for geometric tasks. - Exposure to inference optimization for edge or mobile hardware (TensorRT, ONNX, CoreML, or similar). - Experience with petabyte-scale spatial data: point clouds, meshes, posed image collections, or geospatial indexing. - Background in robotics, augmented reality, 3D reconstruction, digital twins, or autonomous systems. - Prior industry or research internship experience shipping or contributing to a production CV system. Compensation & Benefits The expected salary range for this role is $165,600 - $221,000 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, CA office on a hybrid schedule with a minimum of 3 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 | 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 As a Manager, Compute Accounting at Anthropic, you will execute day-to-day accounting for our compute and cloud infrastructure spend, ensuring accurate financial reporting and robust controls as we scale. You'll be responsible for preparing compute cost accounting, including accruals, prepaids, accounts payable reconciliation, expense classification, and commitment tracking. This role requires hands-on month-end close experience, strong organizational skills, and the ability to build scalable processes and controls in a high-growth environment, with a strong appetite for process improvement and automation. You'll work directly with Engineering, Procurement, and Finance & Strategy to resolve issues and ensure that costs are captured accurately and in compliance with our agreements. As Anthropic's compute footprint expands rapidly across multiple cloud service providers, you'll help operate the financial controls and processes that enable us to manage compute spend measured in the tens of billions of dollars with precision and confidence. You'll also support internal and external audit requests. Key responsibilities Own the accounting lifecycle for compute and cloud infrastructure expenses, ensuring accurate and timely recording of all costs through monthly close, reconciliations, accruals, prepaids, journal entries, and flux analysis Review and interpret cloud service provider and infrastructure contracts to ensure proper accounting treatment, commitment tracking, and compliance with contractual terms Track and reconcile commitment-based agreements, ensuring proper recognition and disclosure of multi-year purchase obligations Perform accounts payable and vendor statement reconciliations, working with cloud service providers to resolve discrepancies and ensure billing accuracy Build scalable processes and controls that can grow with the organization, and develop reporting and monitoring systems to provide visibility into compute spending patterns and trends Support internal and external audit requests on compute cost accounting and commitment disclosure matters Work with Engineering and cloud service providers to investigate issues and see them through to resolution Build monthly and quarterly financial reporting packages for leadership reviews Drive process improvement and automation initiatives—redesigning close workflows, building automated data pipelines and reporting, and leveraging AI tooling—and contribute to cross-functional projects from scoping through delivery Minimum qualifications 7+ years of progressive operational accounting experience CPA (or equivalent) with a strong understanding of GAAP Strong, hands-on month-end close experience, with a proven ability to prepare accruals, reconciliations, and journal entries accurately and on time Significant experience accounting for cloud service or compute infrastructure expenses, including review of associated contracts Experience with cloud service provider cost structures and the unique challenges of accounting for consumption-based services Strong written and verbal communication skills, with the ability to explain issues to vendors, engineers, and other non-finance stakeholders in clear, simple terms Strong analytical abilities and comfort working with a high volume of transactions Proven experience building accounting processes, controls, and policy in high-growth environments Strong organizational skills and attention to detail, with a track record of seeing issues through to resolution Proficiency with modern ERP systems (Workday preferred) Preferred qualifications Have experience mentoring junior accounting professionals A track record of leading process transformation, automation, or finance systems projects from scoping through delivery Strong analytical and problem-solving skills, with the ability to dive deep into large datasets to identify issues and opportunities Comfort with cross-functional partnership in fast-paced environments where priorities can shift quickly SQL and BigQuery proficiency, enabling direct data analysis and validation against source systems Python skills for building automation and analytical tools Experience at cloud service providers, data center operators, or technology companies with consumption-based or usage-based business models Background combining Big 4 accounting experience with industry roles at technology companies Exposure to infrastructure lease or asset structures, including colocation, GPU clusters, networking equipment, or data center buildouts Track record of implementing automated reconciliation and reporting solutions Familiarity with commitment-based purchasing agreements and their accounting implications Proficiency with AI-assisted tools (including Claude) for enhancing financial analysis, memo drafting, and close automation Experience supporting rapid growth and scaling initiatives 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: $160,000 — $190,000 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: San Francisco, CA | New York City, NY 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 As an engineer on this team, you'll sit at the intersection of IT and facilities. You'll build the power models, availability models, topology and load management requirements that operate more efficiently against our physical envelope. Your work will directly shape which sites we lease, what SLAs we sign, how far we oversubscribe, and where workloads are placed. What You'll Do Topology and load management. Own the power and cooling topology of our fleet as a living dataset, validate it and its telemetry against how the buildings really behave, and define how load management behaves under failure across chips and capacity providers, from requirements through commissioning and incident support. Reliability modeling. Build and audit availability models of data center electrical and mechanical systems, define Cloud availability zones and failure domains, from a single site to the whole fleet. Power modeling and load forecasting. Build models of power draw from chip to rack to facility, by workload and hardware generation, and use them to set capacity planning targets, design envelope, and load forecasting. Partner diligence. Work with data center developers, operators, cloud providers and chip vendors to drive design improvements and hold them to SLA-grade performance, with technical diligence on their architectures, reliability studies, rack power specifications and operator interfaces. What We're Looking For Deep knowledge of data center power distribution and cooling architectures, redundancy schemes, and how they interact with IT load profiles. Depth in at least one of: reliability engineering, power modeling and energy scheduling, or load management and controls (telemetry, IT/OT interfaces, load transfer and shedding systems). Familiarity with SCADA/BMS/EPMS, telemetry pipelines, and control systems. Experience with software that bridges IT and OT. Exposure to accelerator deployments and their power management interfaces, or to capacity overallocation in large compute fleets, strongly preferred. Ability to translate between infrastructure engineering, software teams, legal and commercial teams, and external partners. Required Qualifications Bachelor's degree in Electrical Engineering, Mechanical Engineering, Power Systems, Reliability Engineering, Controls Engineering, or a related field 5+ years of experience in data center infrastructure, facility engineering, or reliability engineering Demonstrated experience with data center power distribution and cooling system architectures, and infrastructure failure mode management Demonstrated experience in at least one of the following: Building quantitative reliability or availability models (Monte Carlo, fault tree, reliability block diagram, or FMEA) Building power, energy or capacity models and forecasts from measured data Building, testing or operating software-based power management, load shedding, or control systems Track record of cross-functional collaboration across hardware, software, and facilities teams Preferred Qualifications Experience in more than one of the three focus areas above Experience with accelerator-class deployments, rack power architectures, and their power management interfaces Experience with integrated systems testing and commissioning (L4/L5), or writing sequences of operation Experience with SLA development, availability commitments, or service credit frameworks in leases or cloud contracts Experience with energy storage, microgrid integration, demand response, or behind-the-meter generation Exposure to ML or optimization techniques applied to infrastructure or energy systems 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.

• Develop and adapt computer vision/video analytics models for detection, tracking, and recognition. • Work with video pipelines, including RTSP/HTTP, decoding, sampling, and batching.

— Разработка масштабной системы видеомониторинга и интеллектуальной видеоаналитики. — Техническое лидерство направления Computer Vision.

💎 Разработка CV-моделей для автоматизации складских процессов: детекция, классификация, трекинг, сегментация. Проектирование inference-пайплайнов, включая real-time, и ML-сервисов на Python в микросервисной архитектуре.

Location: Hybrid - San Francisco About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the role We are looking for a Product Manager to join our Product team. You will own Vercel's compute platform — Fluid compute, Vercel Functions, Sandbox, and more — the layer that runs every workload our customers deploy. You will set the direction for how developers configure, scale, and run code on Vercel, from a single function, to multi-service architectures, to agents. You will report to the Product Lead and will be located in San Francisco, CA (hybrid). Vercel invested in its own microVM-based compute infrastructure externally called “Fluid compute”. Fluid changed what’s now possible to run on Vercel. For example, we’ve delivered Sandboxes, a new primitive to run untrusted and agent-generated code. We are just scratching the surface of what Fluid can deliver. This is a senior role with wide latitude: you'll decide where that platform goes next. If you’re based within a pre-determined commuting distance of one of our offices (SF, NY, London, or Berlin), the role includes in-office anchor days on Monday, Tuesday, and Friday. If you're located beyond that distance, the role is fully remote. For location-specific details, please connect with our recruiting team. What you'll do Own the product vision, strategy, and multi-year roadmap for Vercel's compute platform. Define how Vercel serves AI and agent workloads, where long-running, I/O-bound, and code-executing tasks have a fundamentally different compute profile than traditional request/response traffic. Shape the developer experience of running workloads on Vercel: resource model, attributes, API and config files. Partner with Engineering on the performance and reliability bar for compute, including cold starts and creation time latency Define pricing for new products and resources. Set the compute primitives that adjacent product areas build on, and work with those teams on what they need from the platform Work directly with Enterprise customers and the field on compute requirements that block adoption or scale What you need You've built and shipped infrastructure or developer platform products, ideally compute, serverless, containers, or runtime platforms You have the technical depth to reason about concurrency, cold starts, isolation models, and the cost and performance tradeoffs of a compute platform You have owned a platform area that other product teams build on, and set technical direction others adopted You have experience with AI or agent workloads and how their resource profile differs from conventional web traffic You have experience working directly with Enterprise customers on infrastructure requirements You have experience using usage and product analytics data to drive roadmap decisions Bonus if you Have worked at a cloud provider or on a serverless, container, or edge compute platform Have an engineering background or have built software yourself Have worked on multi-runtime platforms and the tradeoffs of supporting several language runtimes Have worked on sandboxing, isolation, or secure execution of untrusted code Compensation & Benefits: Competitive compensation package, including equity. Inclusive Healthcare Package. Learn and Grow - we provide mentorship and send you to events that help you build your network and skills. Flexible Time Off. We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed. The San Francisco, CA base pay range for this role is $208,000 - $312,000. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process. Disclosures: Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data. Equal Opportunity: Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.

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: San Francisco, CA | New York City, NY 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 At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications. Frontier AI runs on datacenters, and the world is in the middle of the largest infrastructure buildout in a generation. The binding constraint on progress is increasingly everything around the chips: land, power, permits, equipment, and the design and construction of the buildings themselves. Bringing a single site online involves hundreds of people, thousands of components, and decisions that move enormous amounts of capital. Much of that work still runs on spreadsheets and handoffs. At Anthropic, we're building software and Claude-powered tools to help Anthropic scale out its compute, and we think there's an enormous opportunity to rethink how that work gets done. It's early, it's already having a real impact, and the engineers who join now will shape how one of the most consequential buildouts in the world gets done. We're looking for strong, versatile software engineers who love building for people doing real work in the physical world. You'll embed with the teams that source sites, design buildings, procure equipment, and manage construction, learn their work deeply, and build the tools and systems they rely on every day. Datacenter experience is a big plus, but what matters most is that you can earn the trust of expert operators, model a messy domain cleanly, and move fast. Responsibilities Build the core systems that track a datacenter's lifecycle (sites, designs, bills of materials, equipment, and construction progress) in one trusted, permissioned source of truth Embed with datacenter, energy, and supply chain teams to understand how the work actually gets done, find the critical path, and build the tools they reach for first Bring order to messy data by migrating and reconciling spreadsheets and legacy trackers, and integrate with the industry's tools, like construction management, scheduling, and engineering systems Design for trust: fine-grained permissions, auditability, and data quality for information that steers major investment decisions Ship early, iterate with users, and cut anything that doesn't help bring compute online sooner Partner with research to understand new model capabilities and share where they fall short in engineering-heavy, physical-world domains You may be a good fit if you Have 8+ years of experience building software, with strong full-stack skills and solid grounding in data modeling, APIs, and databases Have built software that teams in a physical-world industry depend on, such as datacenters, construction, energy, manufacturing, supply chain, or logistics Have a track record of zero-to-one work in startup or startup-like environments Are deeply user-centric: you learn the domain from the people doing the work and validate with them before over-investing Bring high agency and good judgment about what matters, and hold strong opinions loosely Communicate clearly across engineering, operations, and research, and care about the societal impacts of your work Strong candidates may also have Experience in datacenters (at a hyperscaler, colocation provider, operator, utility, or engineering firm), or in adjacent fields like construction, logistics, or legal Experience with the domain's tooling, such as construction management (Procore, Autodesk Construction Cloud), scheduling (Primavera P6), PLM/BOM, ERP and procurement, CAD/BIM, DCIM, or power system studies A background in electrical, mechanical, or civil engineering, energy systems, or supply chain alongside a software career Experience building products with large language models Candidates need not have 100% of the skills listed above Formal certifications or education credentials Direct machine learning or AI research experience Deadline to apply: None. Applications will be reviewed on a rolling basis. 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 — $485,000 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: San Francisco, CA | Seattle, WA | New York City, NY | Washington, DC 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 As part of the Anthropic security department, the compliance team owns understanding security and AI safety expectations, as established by regulators, customers and (nascent) industry norms (which we also seek to influence). The compliance team uses this understanding to provide direction to internal partners on the priorities of security and safety requirements they must meet. The compliance team assures regulators and customers that those expectations are met by earning security credentials and responding to direct inquiry about Anthropics security program from auditors, customers and partners. This opportunity is unique, as we work to secure today’s most novel and valuable asset types, we must build a new kind of compliance program, assuring the safety of artificial intelligence capabilities. Key responsibilities Understand how Anthropic's security and privacy capabilities across major cloud platforms implement common frameworks (e.g., NIST 800-53, NIST 800-171, ISO 27001, ISO 27701, CSA CCM, and SOC 2). Build scalable data center and hyperscaler processes and documentation systems that will support future expansion to additional geographies and compliance frameworks. Assess and mitigate security and operational risks, implementing corrective actions, and managing vendor compliance. Coordinate engagements with independent assessors to earn security and privacy certifications and attestations important to Anthropic customers and enterprise partnerships, and to meet regulatory obligations. Write, update and enact policies capturing security, privacy, and AI safety requirements. Maintain and enhance Anthropic's system of security controls through audit readiness, recordkeeping, and cross-functional communication. Minimum qualifications Have 8+ years of progressive experience in audit and compliance roles, with direct ownership of certification/attestation or security compliance implementation projects Have worked in cloud-native environments and understand security and privacy considerations for multi-cloud and hybrid architectures Can translate complex compliance requirements into actionable workstreams for technical and non-technical stakeholders Have integrated with common controls frameworks or GRC systems that scaled with organizational growth Write clear and useful security and privacy documentation for both external and internal audiences. Thrive in ambiguous, fast-paced environments where you'll need to build processes from scratch Are comfortable organizing time-bounded task management of delegated work streams across a diverse organization Are energized by being the subject matter expert who educates the organization on new compliance requirements and auditors on current security practices Preferred qualifications Have worked in AI/ML companies and understand unique security considerations for model development and deployment Have worked with cloud companies and understand cloud security controls and physical security requirements Bring experience from high-growth technology companies managing rapid compliance expansion Have some experience implementing automated enforcement of security controls (i.e., compliance as code) Possess relevant certifications (CISA, CRISC, CISM, CISSP, or ISO 27001 Lead Auditor/Implementer) 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: $270,000 — $345,000 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: Paris; San Francisco 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. Mistral AI is building a new Compute Support team to ensure the reliability, performance, and scalability of our GPU clusters in a Kubernetes environment. As one of the founding members of this team, you will play a pivotal role in shaping its processes, standards, and culture. In this hybrid L1/L2 support role, you will be the first point of contact for customers and internal teams, providing technical guidance, troubleshooting, and issue resolution for compute-related inquiries. You’ll also serve as the escalation point for complex issues, leveraging your deep systems knowledge, Kubernetes expertise, and operational debugging skills to ensure our AI workloads run smoothly at scale. This is a support-focused role that blends system administration, customer-facing communication, and compute infrastructure expertise. While coding is not the primary focus, familiarity with Go for debugging and automation is a plus.     KEY RESPONSIBILITIES FIRST CUSTOMER’S POINT OF CONTACT - Act as the first interlocutor for customers and internal teams, providing timely and effective responses to compute-related inquiries. - Triage and prioritize incoming requests, ensuring SLAs are met for acknowledgment, first response, and resolution. - Gather and analyze initial issue details (e.g., logs, error messages, system metrics) to diagnose problems efficiently. - Provide clear, actionable guidance to customers and internal users, including temporary workarounds where applicable.     TECHNICAL SUPPORT - Serve as the L2 escalation point for Linux, Kubernetes, and compute infrastructure issues, providing deep technical troubleshooting for: - GPU/TPU workloads (e.g., CUDA errors, memory leaks, job failures). - Kubernetes clusters (e.g., pod crashes, node failures, networking misconfigurations). - Bare metal and cloud environments (e.g., AWS EC2, GCP VMs, HPC clusters). - Diagnose and resolve performance bottlenecks, hardware failures, and resource contention in distributed systems. - Analyze system metrics, logs, and traces (e.g., dmesg, journalctl, nvidia-smi, Prometheus, Grafana) to identify root causes of issues. - Participate in on-call rotations to provide 24/7 support for critical compute systems - Nice to have: Optimize system configurations (e.g., kernel parameters, filesystem tuning, network settings) for high-performance computing (HPC) and AI workloads.     KUBERNETES & CONTAINERIZATION - Debug Kubernetes clusters with a focus on: - Pod and node issues (e.g., CrashLoopBackOff, OOMKilled, ImagePullBackOff). - Networking and storage (e.g., CNI plugins, PersistentVolumes, StorageClasses). - Resource management (e.g., Requests/Limits, QOS classes, node affinity). - Troubleshoot container runtime issues (Docker, containerd) such as image pull failures, OCI compliance, or runtime errors. - Collaborate with SRE teams to understand and improve existing IaC (Terraform, Ansible) and Go-based tooling.     DOCUMENTATION & PROCESS IMPROVEMENT - Create and maintain runbooks, playbooks, and internal documentation for common compute issues (e.g., GPU debugging, Kubernetes troubleshooting). - Contribute to post-mortems with actionable follow-ups to prevent recurring incidents. - Train internal teams on best practices for compute infrastructure and debugging. - Help define and refine support processes as a founding member of the new Compute Support team. What We’re Looking For REQUIRED SKILLS & EXPERIENCE - 5+ years of experience in system administration, technical support, or infrastructure operations, with a strong focus on compute-heavy environments (bare metal, cloud, HPC, or virtualization). - Deep Linux/Unix expertise: - Debugging kernel-level issues (e.g., OOM killer, I/O bottlenecks, CPU throttling). - Performance tuning (e.g., sysctl, ulimit, filesystem optimizations). - Networking troubleshooting (e.g., iptables, tcpdump, DNS, NFS, SSH). - Storage management (e.g., LVM, RAID, NVMe, GPU-local storage). - Hands-on Kubernetes experience is mandatory: - Debugging pods, nodes, and clusters (e.g., kubectl describe, kubectl logs, crictl). - Networking and storage (e.g., CNI plugins, PersistentVolumes). - Resource management (e.g., Requests/Limits, QOS classes). - Familiarity with containerization (Docker, containerd) and basic IaC awareness Proficiency with monitoring tools (Prometheus, Grafana, ELK, OpenTelemetry). - Basic scripting/automation skills (preferably Go, but Bash or Python are acceptable for ad-hoc tasks). - Experience with bare metal, virtualization, or HPC environments (e.g., Fluidstack, Coreweave, Vast) is a strong plus. - Excellent problem-solving and communication skills, with the ability to explain technical issues clearly and patiently to both technical and non-technical stakeholders. - Customer-focused mindset with a passion for resolving issues efficiently and improving system reliability. - Ability to work in on-call rotations and handle high-pressure situations with a structured, calm approach. - Commitment to meeting tight SLAs for issue acknowledgment, triage, and first response. 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; Sunnyvale, CA Workplace: Hybrid At Niantic Spatial, we’re building the future of physical AI. Powered by a proprietary database of over 30 billion posed images, our groundbreaking mapping technology unlocks a new dimension of interaction and spatial intelligence that helps both humans and machines better understand, represent, navigate, and engage with the real environment. Join us as we build the real-world foundational models for physical AI, so people and machines can work efficiently and safely together. As a Senior Computer Vision Engineer on the Applied Algorithms team, you will own significant parts of our Localization technology. As a member of this team, you will be responsible for building the Map representing a living geospatial world model, as well as the centimeter-level accuracy Visual Positioning System (VPS) that allows people and robots to explore the real world. Part of the role will be bridging the gap between R&D and production, turning complex geospatial data into a persistent sense of space and enabling the next generation of spatial AI. RESPONSIBILITIES - System Architecture: Design, develop, and maintain production-grade computer vision systems that power Niantic Spatial’s VPS (Visual Positioning System) and 3D mapping pipelines. - Algorithmic Innovation: Refine and scale algorithms for our VPS system including, SfM (Structure from Motion) and Feed Forwards models, efficient feature and descriptor extraction to have the best possible accuracy and recall. Moving algorithms from research concepts to hardened production code that can scale for our map of the world. - Performance Engineering: Optimize complex ML and CV code for maximum efficiency in cloud and mobile environments, ensuring low latency and high-performance execution on GPU/CPU. - Benchmarking & Evaluation: Create and own the tools and frameworks used to evaluate the quality of our spatial grounding and 3D maps against ground-truth data. - Technical Leadership: Lead technical design reviews, mentor junior engineers, and serve as a team anchor for resolving complex technical disagreements within the mapping stack. - Cross-Functional Delivery: Collaborate with Product, Research, and Operations teams to ensure that state-of-the-art computer vision solutions translate into delightful user experiences. REQUIREMENTS - Education: BS, MS, or PhD in Computer Science, Robotics, Computer Vision, or a related technical field (or equivalent professional experience). - Years of Experience: 5+ years of experience developing and shipping algorithms for image processing, computer vision, or 3D reconstruction. - Coding Proficiency: Expert-level proficiency in python and/or C++. - Domain Expertise: Proven track record in designing solutions for Structure from Motion (SfM), VPS or 3D mapping.. - Frameworks & Tools: Deep experience with Deep Learning frameworks (PyTorch or JAX) and version control (Git). - Required in-office days: 3 days per week Plus If: - Experience in planning and leading technical projects from inception to production. - Significant contributions to open-source CV libraries (OpenCV, COLMAP, etc.). - Experience with CUDA or shader programming for performance optimization. Candidate Privacy Policy 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. If required by law, by submitting my job application I consent to the processing of my information as described in that Notice, including processing information I voluntarily disclose to Niantic Spatial, such as health or medical information, race or ethnicity data, and sexual orientation data and, in limited circumstances sharing information with third parties such as references and other third parties that assist in the hiring process. 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.

Location: Philippines Workplace: Remote ABOUT THE ROLE The Compute & Infrastructure Accounting team supports accounting and financial reporting for OpenAI’s rapidly evolving cloud computing, data center, server, equipment, colocation, software and data, and other AI infrastructure arrangements. We’re seeking a hands-on Contract Accountant to support recurring close and day-to-day operational accounting for these costs. The contractor will translate contract terms, pricing, delivery, usage, invoices, and operational data into accurate accruals, true-ups, journal-entry support, reconciliations, and variance explanations. This role works closely with Compute & Infrastructure Accounting, Technical Accounting, Procurement, Strategic Finance, Data Engineering, and external vendors to resolve exceptions and keep accounting outputs timely, complete, and audit-ready. The contractor will use approved AI tools to reduce manual effort, strengthen analysis, improve documentation, and create scalable operating leverage. This role does not make final accounting conclusions or approve journals, payments, vendors, contracts, or access; it does not negotiate contracts or commit company funds. Success is measured by accurate and timely close deliverables, well-supported reconciliations, prompt exception resolution, dependable cross-functional communication, and adherence to established controls. RESPONSIBILITIES LEASE AND FIXED ASSET ACCOUNTING - Own assigned month-end and quarter-end lease-accounting activities, including journal entries, rollforwards, account reconciliations, balance-sheet substantiation, and flux or variance analysis. - Prepare complete, accurate, and reviewer-ready journal entries and supporting schedules for lease-related balances, including right-of-use assets, lease liabilities, rent expense, interest, amortization, remeasurements, and true-ups. - Perform reconciliations over lease accounts and subledger-to-general-ledger balances; investigate reconciling items, document conclusions, and drive timely resolution. - Perform fixed-asset accounting as assigned, including additions, transfers, placed-in-service assessments, depreciation, disposals, construction-in-progress activity, reconciliations, and period-end entries. CONTRACT REVIEW AND LEASE-SYSTEM ADMINISTRATION - Read and analyze large, complex lease contracts, amendments, renewals, extensions, and termination agreements to identify relevant accounting terms, payment streams, options, incentives, obligations, and effective dates. - Accurately enter new leases, modifications, remeasurements, and terminations into the lease-accounting system based on a complete understanding of the underlying contract. - Validate lease-system inputs and outputs against executed agreements, payment schedules, invoices, commencement evidence, and operational data; resolve completeness and accuracy exceptions. - Compile and validate information supporting quarterly and annual lease footnote disclosures, including maturity analyses, expense classifications, weighted-average metrics, cash-flow information, and required tie-outs. CONTROLS, AUDIT, AND ISSUE RESOLUTION - Follow U.S. GAAP, established lease-accounting and fixed-asset policies, standard operating procedures, close calendars, review requirements, and approval workflows. - Execute control procedures over lease populations, contract abstraction, system inputs, calculations, reconciliations, disclosures, and workpapers, including completeness and accuracy checks and evidence retention. - Respond to internal and external audit requests by assembling contracts, tie-outs, schedules, explanations, control evidence, and other supporting documentation. - Investigate accounting and control exceptions, document root causes and resolutions, track open items through completion, and escalate significant matters promptly. CROSS-FUNCTIONAL COORDINATION - Partner with Compute & Infrastructure Accounting, Technical Accounting, Finance Systems, Data, Engineering, and business teams to resolve contract, data, system, accounting, and operational issues. - Coordinate with Legal, Procurement, FP&A, Accounts Payable, Treasury, and other stakeholders to obtain executed agreements, validate facts, and support complete and timely lease accounting. - Communicate requirements, status, outstanding items, and accounting implications clearly to finance and non-finance stakeholders, and escalate judgmental matters with clear context and recommended next steps. PROCESS DISCIPLINE AND CONTINUOUS IMPROVEMENT - Identify recurring contract, data-quality, system, process, and control issues; surface trends and recommend scalable improvements. - Write clear business requirements, test lease-system or process changes, and validate downstream accounting outputs before operational use. - Improve recurring lease and fixed-asset workflows through standardization, documentation, automation, and tooling; maintain clear procedures and handoffs. - Use approved AI-enabled tools responsibly to support contract review, data validation, analysis, and documentation while following data-security and review requirements. - Help maintain consistent, controlled execution as the infrastructure portfolio, accounting requirements, systems, and workflows evolve. REQUIRED SKILLS AND EXPERIENCE - Progressive experience in accounting, audit, advisory, or a related finance function, including hands-on operational accounting and ownership of recurring close deliverables. - Strong month-end and quarter-end close experience involving journal entries, account reconciliations, rollforwards, variance analysis, and reviewer-ready workpaper preparation. - Strong working knowledge of U.S. GAAP and internal controls, with the judgment to identify and escalate matters requiring technical accounting review. - Demonstrated ability to read and interpret lengthy, complex contracts and translate legal and commercial terms into accurate accounting conclusions, system inputs, and supporting documentation. - Advanced spreadsheet and data-analysis skills, including the ability to work accurately with large datasets, and experience using an ERP or comparable finance system. - Experience operating with high attention to detail in a fast-paced, deadline-driven environment while managing multiple agreements, systems, and stakeholders. - Strong analytical, problem-solving, and organizational skills; sound judgment; and clear documentation habits. - Excellent written and verbal communication skills and the ability to partner effectively across accounting, finance, legal, systems, data, engineering, and business teams. PREFERRED - Hands-on lease-accounting experience under ASC 842, including contract abstraction, classification, measurement, modifications, reconciliations, and disclosure support. - Hands-on fixed-asset accounting experience, including additions, depreciation, disposals, transfers, construction in progress, and related reconciliations. - Experience with lease-accounting software and an ERP such as Oracle Fusion; CPA, CA, or an equivalent professional accounting qualification is a plus. - Experience preparing or reviewing cash flow statements, including cash flow classification and presentation for lease and fixed-asset activity. NICE-TO-HAVE - Experience in a technology, cloud-computing, data-center, colocation, equipment, or other infrastructure-intensive environment. - Familiarity with SQL, data-query tools, issue-tracking tools, or similar technical tools used to investigate data, system, and process issues. - Experience supporting SEC reporting, lease footnote disclosures, or public-company audit requirements in a high-growth or control-focused environment. - Experience with process automation, systems implementation, or workflow redesign, and collaborating across time zones with distributed teams and external service providers.

Задачи: — Руководить командой Computer Vision Engineers — Проектировать архитектуру production AI-систем — Менторить инженеров и проводить code review — Декомпозировать задачи и контролировать качество реализации — Разрабатывать пайплайны обработки десятков и сотен RTSP-потоков — Оптимизировать инференс на GPU и CPU — Принимать ключевые технические решения — Участвовать в найме и развитии AI-команды Основной стек: Python, PyTorch, OpenCV, YOLO, RTSP, GStreamer, NVIDIA DeepStream, TensorRT, Triton Inference Server, ONNX, OpenVINO, CUDA, FastAPI/gRPC, Docker и Kubernetes. Что важно: ✅ Сильный коммерческий опыт в Computer Vision и Video Analytics ✅ Опыт технического лидерства или менторства ✅ Запуск production AI-систем ✅ Уверенное знание Python, PyTorch, OpenCV и YOLO ✅ Практический опыт с RTSP, GStreamer, DeepStream и TensorRT ✅ Оптимизация моделей через ONNX, TensorRT, OpenVINO, CUDA или Quantization ✅ Понимание высоконагруженной обработки видеопотоков ✅ Умение принимать и аргументировать архитектурные решения Будет плюсом: ➕ Triton Inference Server ➕ C++ и CUDA ➕ Kafka и потоковая обработка данных ➕ MLflow и MLOps ➕ ViT, DETR, Swin и Video Transformers ➕ VLM, RAG, LangGraph, vLLM и Function Calling ➕ Опыт найма и формирования AI-команд Предлагаем влияние на архитектуру и технологический стек, сильную инженерную команду и работу над высоконагруженной системой промышленного уровня.