Инженер компьютерного зрения вакансии

Location: San Francisco, CA; Sunnyvale, 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. THE OPPORTUNITY As a staff member of the Map Team, you’ll own and drive significant parts of our Reconstruction and/or Localization technologies. You will be responsible for building the Map representing a living geospatial world model that can be simultaneously used to generate a high-fidelity 3D representations via Gaussian Splatting and Meshing, as well as the centimeter-level accuracy Visual Positioning System (VPS) that allows people and robots to explore the real world. This is an individual contributor role with a strong component of technical leadership where you will mentor other engineers and influence the technical roadmap. WHAT YOU WILL DO - Technical Leadership: Lead the design and implementation of some of our core technologies, namely, Structure from Motion (SfM), Feed Forward and Foundational models, and high-fidelity 3D Reconstruction (e.g. meshing, gaussian splats). - Applied Research: Up to speed state-of-the-art in relevant areas to be able to invent novel solutions in VPS and/or 3D Reconstruction alongside the team. - System Architecture: Design, develop, and maintain scalable production-grade Computer Vision systems that power Niantic Spatial’s VPS, 3D Reconstruction and 3D Mapping pipelines. - Algorithm optimization and production implementation: develop and optimize algorithms, train models, for high-accuracy and high-performance execution on CPU/GPU on the cloud or device as part of a reliable production system. - Quality & Benchmarking: Drive decision-making creating high quality data that allows the accurate spatial grounding of AI queries with structural, semantic and location specific knowledge. - Technical Strategy & Mentorship: Work with engineering leadership to define the technical roadmap and quarterly objectives for the Applied CV Team; provide high-level mentorship and code governance to elevate the team’s technical bar. - 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. WHAT WE ARE LOOKING FOR - Years of Experience: 7+ years of professional experience in Computer Vision, Machine Learning, or a related field (or 4+ years with a PhD in a relevant domain). - Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field; Master's or PhD preferred. - Core Technical Skills: Strong proficiency in Python and/or C/C++. - Specialized Expertise: Proven experience in both classical and learned-based 3D Computer Vision and ML. - Full SW lifecycle experience: Demonstrated experience in taking research into production at scale. - Technical Leadership Experience: Previous experience tech leading computer vision projects. COMPENSATION & BENEFITS The expected salary range for this role is $256,500 – $315,000 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 or Sunnyvale 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 You'll help build the geometric foundation of the next-generation world map — joining our World Map Research Engineering team (Geospatial Alignment) as a Research Engineer or Senior Research Engineer. This is an end-to-end applied research role that spans from strong engineering and data-systems work to R&D in 3D deep learning, transformers, and foundation models. You'll develop new algorithms, produce the research data and evaluation assets needed to advance them, and engineer the resulting capabilities into dependable production systems. The World Map team works with heterogeneous captures from phones and handheld devices, aerial imagery, LiDAR, and 360 cameras, as well as external geographic and elevation data. The central challenge is to harmonize these data sources, quantify uncertainty, and maintain consistency as the map evolves. You'll work at the intersection of cutting-edge research and scalable engineering — developing new approaches to geospatial registration, correspondence, and geometric optimization, then productionizing these technologies to directly improve Niantic Spatial's world model. What You'll Do - Geospatial Registration — Develop and advance algorithms for world-scale georeferencing and registration across imagery, 3D reconstructions, point clouds, and geographic reference data. - 3D Geometry & Correspondence — Build and improve methods spanning multi-view geometry, SfM, SLAM, feature matching, learned correspondence, bundle adjustment, point-cloud registration, and ICP. - Data & Evaluation — Create the data and evaluation flywheel for world-scale mapping — design and maintain large-scale datasets, pipelines, benchmarks, and evaluation methodologies that expose hard failure modes, accelerate research iteration, and support production. - Learning-Based 3D Reasoning — Explore and develop learning-based approaches for geospatial understanding, combining transformers and 3D foundation models with geometric priors and uncertainty modeling. - Production Robustness — Design robust solutions for challenging real-world conditions: sparse or noisy GPS, changing appearance, inconsistent reconstruction quality, large geographic extents, and imperfect reference maps. - Cross-Functional Collaboration — Partner with leading researchers in visual localization, 3D computer vision, and mapping — as well as engineering and product teams — to identify high-impact problems and turn research breakthroughs into end-to-end production systems. - Research Communication — Share results clearly through technical writing, design reviews, and internal presentations; contribute to publications and open research where appropriate. WHAT YOU'LL BRING - Bachelor's or Master's degree in Computer Science, Robotics, Machine Learning, Photogrammetry, or a closely related field — or equivalent research or industry experience. - Strong grounding in 3D computer vision, machine learning, robotics, photogrammetry, or a closely related area. - Demonstrated experience with 3D geometry and several relevant areas — multi-view reconstruction, SfM, SLAM, camera pose estimation, point-cloud registration, image-based localization, georeferencing, or sensor fusion. - The ability to formulate ambiguous real-world problems, choose the right mathematical or learning-based tools, and evaluate solutions rigorously. - Strong Python skills and experience with modern ML and scientific-computing libraries (PyTorch, NumPy, SciPy). - Strong software engineering skills — you can turn research prototypes into reliable, scalable, and maintainable systems. - A track record of taking an algorithm from research idea and experimental prototype through evaluation, benchmarking, and deployment on real-world data. - Clear written and verbal communication; able to collaborate effectively across research and engineering disciplines. NICE TO HAVE - PhD in computer vision, robotics, machine learning, photogrammetry, geodesy, remote sensing, or a related field — not required, but valued. - A strong publication record or active involvement in the research community at venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, SIGGRAPH, 3DV, ICRA, or RSS. - Experience with learning-based approaches for visual or 3D understanding — transformers, point transformers, foundation models, or methods combining learned representations with explicit geometric priors. - Experience with aerial or satellite imagery, GNSS/GPS, geodesy, mapping systems, or large-scale spatial data. - Evidence of technical leadership, mentorship, or successful cross-functional delivery. COMPENSATION & BENEFITS Base salary: Competitive market rate. 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. We welcome applications from candidates who require visa sponsorship. 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 We are looking for 3D Reconstruction Research Scientist to join our Research Team in London. Our team researches and builds the 3D reconstruction technology behind Niantic Spatial's platform. These pipelines turn casually captured or domain specific imagery into high-fidelity explorable 3D reconstructions. This entails anything from Structure-from-Motion through to 3D Gaussian Splatting, feed-forward models, and generative models. Our team shipped 360 splatting to consumers and enterprise customers, developed the splatting tech that runs on phones, shipped multiple POCs to enterprise customers, and have innovated on countless AR technologies. Our team has published at top venues (CVPR, ICCV, ECCV, SIGGRAPH); more often than not, our papers end up in production. We're hiring a researcher to work at both ends of that pipeline. You will implement and iterate on the state-of-the-art for both academic publishing and production, regularly working on prototypes with a short turnaround into customer-facing production. You will work alongside world-class researchers in computer vision, machine learning, graphics, and robotics to develop new approaches for large-scale spatial understanding, localization, reconstruction, scene understanding, and geospatial foundation models. WHAT YOU’LL DO - Conduct original research in computer vision, machine learning, and spatial AI. - Design, implement, and evaluate novel algorithms for: - 3D reconstruction - Neural scene representations - 3D Gaussian Splatting - Geometric deep learning - Structure-from-Motion (SfM) - Meshing - Feed-forward models - Generative models - Spatial foundation models - Collaborate with research scientists and engineers to transition promising ideas into future products. - Develop large-scale experiments and benchmarking frameworks. - Work directly with the realities of production with real capture conditions, real hardware constraints, and real customers. - Publish research findings at leading conferences such as CVPR, ICCV, ECCV, or SIGGRAPH. WHAT YOU’LL BRING - PhD in Computer Vision, Robotics, Machine Learning, Computer Science, Mathematics, Physics, or a closely related field. Exceptionally strong candidates with equivalent experience in industry would be considered. - A strong research track record in 3D computer vision: reconstruction, depth estimation, novel view synthesis, SfM, SLAM, or closely related areas. - Strong publication record at top-tier conferences such as CVPR, ICCV, ECCV, SIGGRAPH, NeurIPS, etc. - Strong programming skills in Python and experience in PyTorch. - Evidence that you can carry an idea from research into something real; that may be a shipped feature, a production pipeline, a widely used open-source release, or similar. - Ability to independently drive research projects from idea generation through experimentation and publication. NICE TO HAVE - Experience with classical reconstruction tooling (COLMAP or similar). - C++ or CUDA experience, and a feel for performance and on-device constraints. - Experience with traditional 3D techniques — meshing, texturing, or bringing modern geometry or generative representations into native 3D. COMPENSATION & BENEFITS Base salary: Competitive market rate. 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.

• 5+ лет опыта в Computer Vision и Deep Learning. • Глубокая экспертиза в Python и современных CV-фреймворках.

Ищем CV-инженера в облачную платформу, которая помогает рентгенологам описывать КТ и МРТ быстрее и точнее. Основной проект — генерация заключений по КТ органов грудной клетки: от классических 3D-сервисов сегментации и классификации патологий до использования LLM и обучения VLM для КТ.

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

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; 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.

О проекте Промышленная видеоаналитика. Ядро уже работает - детекция, трекинг, распознавание лиц, детектор СИЗ, API и веб-интерфейс. Нужно довести систему до продакшн внедрения. Задачи: - Довести распознавание лиц до измеримого качества: разметка, калибровка порогов, метрики FAR/FRR - Устойчивое отслеживание - Оптимизация производительности пайплайна под CPU-only сервер для оффлайн обработки - Обучение и дообучение детекторов на собственных данных, организация разметки Требования - Уверенный Python + Go, опыт с ONNX/ONNX Runtime (экспорт, opset, оптимизация latency на CPU, а не GPU serving) - Опыт с YOLO - Face detection/recognition пайплайны (детектор + embedding + порог по cosine similarity) - Опыт с OpenCV DNN/Zoo моделями плюс - Object tracking (IoU/ByteTrack-подобные трекеры, multi-object tracking metrics, ID switches)

Задачи: — разрабатывать и внедрять современные решения в области компьютерного зрения Требования: — опыт коммерческой разработки в области Computer Vision от 3 лет — хорошее понимание классического машинного обучения, статистического анализа, классических алгоритмов Computer Vision — практический опыт работы с нейросетевыми фреймворками PyTorch — умение читать научные статьи, воспроизводить решения и адаптировать их под реальные задачи — уверенное владение библиотеками NumPy, scikit-learn, Matplotlib, OpenCV — уверенная работа с Linux (предпочтительно Ubuntu, Mint или Debian) — опыт контейнеризации с использованием Docker и Docker Compose — уверенное владение Git — английский язык — Upper-Intermediate (B2) или выше (обязательно) — наличие проектов, которые были самостоятельно доведены до production Будет преимуществом: — опыт разработки систем видеоаналитики и/или видеонаблюдения — опыт оптимизации скорости инференса моделей с использованием ONNX Runtime и TensorRT — практический опыт работы с Graph Neural Networks (GraphNN/GNN) и Metric Learning — опыт работы с Kubernetes (K8s) Мы ищем человека, который: — любит решать сложные инженерные задачи — следит за современными исследованиями в области AI и Computer Vision — умеет самостоятельно принимать технические решения и доводить проекты до результата — готов работать над задачами полного цикла — от исследования и прототипирования до внедрения в production

Задачи: — Проектировать и развивать модели компьютерного зрения и видеоаналитики (детекция, трекинг, распознавание лиц, анализ поведения); — Интегрировать ML-модели в production (backend, edge); — Обучать и дообучать модели (fine-tuning, transfer learning); — Работать над реальными AI-проектами с бизнес-применением; — Сопровождать полный цикл разработки: от исследования до деплоя; — Оптимизировать модели и повышать качество CV-решений. Требования: — Уверенные знания Computer Vision и современных DL-подходов; — Глубокое понимание машинного обучения и нейронных сетей (CNN, detection/segmentation); — Уверенное владение Python; — Опыт работы с OpenCV, NumPy, PyTorch и/или TensorFlow; — Опыт работы с Git; — Опыт оптимизации моделей (speed/accuracy trade-offs, inference); — Опыт решения задач детекции, трекинга и анализа поведения людей. Условия: — Формат работы: офис, Астана.

About the role We’re building a high-performance computer vision system that detects and recognizes objects on fast-moving trains and trucks. The application runs on Linux and is built with Rust/C++ and OpenCV. You’ll join a small team of engineers and ML specialists, working directly with the technical lead on software that powers logistics, automation, tracking, and access control for ports, railways, and industrial facilities. This is not an ML research role. Our ML team trains the models—you’ll focus on everything around them: recognition quality, algorithms, tooling, performance, and developer experience. What you’ll do Improve recognition quality through data analysis and application logic Build internal tools, scripts, and developer utilities Refactor and optimize existing systems for performance and stability Contribute to other engineering projects when needed (web, mobile, embedded, infrastructure) Depending on the project, you may also work with Go, Python, React/TypeScript, SQL/Postgres, and Linux tooling. We’re looking for someone with Strong Rust, C++, or equivalent systems programming skills Solid Linux, Git, and command-line experience Basic understanding of ML or data analysis Good written and spoken English We value engineers who are curious, take ownership, debug systematically, communicate well, and enjoy solving challenging real-world problems. Nice to have OpenCV, CUDA, deep learning, or custom ML model training Linux internals, performance optimization, or low-level debugging Docker, networking, distributed systems, or embedded development Strong personal or open-source projects Why Bravora? We’re a small, fully remote engineering team where you’ll have real ownership, direct impact, and plenty of room to grow. We actively modernize our stack, encourage AI-assisted development, and provide access to state-of-the-art LLM tools. Interested? Send us your CV, GitHub or portfolio (if available), your earliest start date, expected hourly rate, and a few sentences about why this role interests you.

Location: Riyadh, Saudi Arabia Join Müller's Solutions as an AI / Computer Vision Engineer and be part of a dynamic team that is transforming industries through advanced technology. In this role, you will design, develop, and implement computer vision and AI models that address complex challenges and drive innovation in our products and services. Key Responsibilities: Develop and deploy state-of-the-art computer vision algorithms for various applications. Collaborate with product teams to understand requirements and translate them into technical specifications. Analyze large datasets to extract insights and improve model performance. Test and validate AI solutions to ensure high accuracy and reliability. Participate in code reviews and contribute to best practices in software development. Keep abreast of the latest advancements in AI and computer vision and integrate relevant technologies into existing systems. Research and present findings on new methodologies and approaches in the field. Requirements Qualifications: Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field. Proven experience in AI and computer vision technologies, including deep learning frameworks (e.g., TensorFlow, PyTorch). Strong programming skills in Python and familiarity with OpenCV. Experience with data handling, preprocessing, and training machine learning models. Solid understanding of algorithms and data structures. Familiarity with cloud computing platforms and tools. Exceptional problem-solving skills and the ability to work in a collaborative environment. Strong communication skills to effectively convey complex ideas to both technical and non-technical stakeholders. Benefits Why Join Us: Opportunity to work with a talented and passionate team. Competitive salary and benefits package. Exciting projects and innovative work environment.

Location: Riyad, Saudi Arabia As an AI / Computer Vision Engineer at Müller's Solutions, you will have the opportunity to work on cutting-edge projects that leverage artificial intelligence and computer vision technologies. You will collaborate with cross-functional teams to develop innovative solutions that solve complex business challenges using AI and computer vision algorithms and techniques. Responsibilities: Design and develop AI and computer vision solutions for various industries and use cases. Implement and optimize computer vision algorithms for object detection, image recognition, and image segmentation. Train and fine-tune machine learning models using large datasets. Collect and preprocess data for training and validation purposes. Integrate AI and computer vision solutions into existing systems and platforms. Perform testing and debugging of AI and computer vision models and systems. Stay current with the latest advancements in AI and computer vision technologies. Building Computer Vision AI models including all pre-processing and post- processing Ownership of the Entire Solution Daily Updates Knowledge sharing Requirements Requirements: Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience in AI and computer vision development. HANDS ON PYTHON AND DATABASES( SQL AND NOSQL), Open CV COMFORTABLE WITH LINUX Experience with data preprocessing and data augmentation techniques. Knowledge of software development practices and version control systems. Excellent problem-solving and analytical skills. Ability to work independently and in a team environment. Good communication and collaboration skills.