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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.

SpAItial is looking for a Research Scientist 3D Reconstruction and Novel View Synthesis to advance and evaluate 3D reconstruction and view-synthesis methods.

Задачи: — разработка, оценка и внедрение передовых методов 3D-реконструкции.

Location: Abu Dhabi, United Arab Emirates Workplace: hybrid Autonomous vehicles are coming to the markets in which inDrive serves, but the AV industry has a blind spot: it has almost no data from the cities where we operate. inDrive runs one of the world's largest ride-hailing fleets, concentrated in exactly the emerging markets global AV players have yet to reach. We are building the team that turns that fleet into an AV grade data platform: large scale multi sensor collection from real vehicles on real trips, evaluation of driving models against human drivers, automated and human in the loop causal annotation, and camera first 3D scene reconstruction for simulation. We are hiring the founding leader of this workstream. This is a rare true zero to one: you will hire the team, stand up the vehicles and the data platform, set the technical bar, and own delivery end to end. Key Responsibilities Own the AV data workstream end to end. Roadmap, execution, quality, and outcomes, from vehicle data capture through processing, annotation, and delivery of AV-grade datasets Build the team from zero. Hire and lead a multi disciplinary team covering large scale data engineering, search and serving, ML engineering across divergence detection, edge inference, and VLM based auto labeling, 3D reconstruction research, and data annotation operations. Own the hiring bar and the team's growth Management : Manage ML engineers' charter across the cluster Set technical direction across disciplines. Provide design authority for the full pipeline, including onboard capture, cloud ingestion and processing at fleet scale, semantic and causal labeling, and neural scene reconstruction, and make the key technical decisions on evidence Partner with leaders across the organization. Work closely with the leaders of data platform, ML ops, geo and mapping, and inDrive's wider autonomous vehicle initiatives to align roadmaps, share infrastructure, and unblock delivery Own external partnerships. Drive the technical relationships this work depends on, including the NVIDIA AV ecosystem and prospective AV partners consuming our data Balance research and delivery. Several of the core questions here are open research. You frame milestones as decision gates, redirect work based on evidence, and keep the team shipping measurable results on a schedule Skills, Knowledge and Expertise 10+ years of engineering experience in applied ML, autonomous systems, or large-scale data and ML platforms, including 3+ years in the autonomous vehicle industry or closely adjacent autonomy domains (AV data, simulation, or evaluation platforms, ADAS, robotics perception, HD mapping), and 4+ years managing engineering teams, with a track record of building teams from scratch and delivering from zero to one Strong command of the modern AV and foundation model landscape: vision-language models, multi-modal perception, 3D reconstruction and neural rendering, and the NVIDIA AV ecosystem. Deep enough to set direction, review designs, and make evidence-based technical calls Genuine engineering leadership range: you have successfully led data engineering, platform, or infrastructure delivery, not only ML research, and can evaluate and unblock work across those disciplines Proven ability to take large-scale ML systems from conception to production: data pipelines, training and evaluation infrastructure, and models running under real-world constraints Strong external presence: experience owning technical partnerships, vendor and licensing relationships, or customer-facing technical engagements at a senior level Deep fluency in the modern ML stack (PyTorch or equivalent, large-scale training and inference, Python and Linux) and in cloud data platforms at multi-terabyte scale Bachelor's degree in Computer Science, Engineering, or a related field Nice to have: AV industry experience specifically in offline evaluation, data mining, annotation platforms, or simulation, as distinct from on-vehicle stack development Advanced degree (MS or PhD) in ML, robotics, or computer vision Experience operating in emerging markets, and comfort building where the playbook does not exist yet Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects Work alongside people who take initiative, speak openly, and challenge themselves to grow Improve your language skills through co-financed courses and internal speaking clubs Final benefits may vary depending on the location.

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.

-Разрабатывать computer vision и machine learning решения для архитектурных чертежей, технических документов, CAD и BIM-данных. -Строить пайплайны, объединяющие растровые изображения, векторную геометрию, структурированные инженерные данные, OCR и ML-модели.

Location: Baku, Azerbaijan; Ganja, Azerbaijan; Sumqayit, Azerbaijan; Mingachevir, Azerbaijan; Khirdalan, Azerbaijan Do you enjoy precise, detail-oriented work and have an eye for spatial accuracy? This role puts those skills to use on a project at the intersection of geospatial data and AI. As a Data Annotator on our project, you will support building digital 3D models of power grids and other critical infrastructure. These models help energy companies analyze network conditions, predict risks, and plan maintenance using AI and physics-based simulations. You will help reconstruct electrical distribution networks in 3D by combining LiDAR point cloud data, GIS maps, and drone imagery – contributing directly to the accuracy and reliability of these digital twins. What you’ll be doing: Reconstructing 3D power grid networks using point cloud (LiDAR) and map (GIS) data; Placing 3D objects (poles, lines, conductors) to match real-world physical layouts; Aligning original 2D map data with 3D models; Labeling high-resolution drone photos to identify grid components and detect structural defects (e.g., equipment damage or wear). Requirements: Strong spatial reasoning and the ability to easily navigate 3D environments; English B1 (ability to read instructions, watch training videos, and communicate with teammates); High attention to detail, problem-solving skills, and a willingness to learn from feedback; PC/laptop with an Intel i7-11800H (or equivalent/better CPU), dedicated GPU (NVIDIA T1200 or better; RTX 4060 recommended), and 16 GB RAM minimum (32 GB preferred). Will be a plus: Any basic understanding of power grids (poles, transformers, wires) or prior experience with LiDAR data; Background in GIS, Geodesy, Cartography, Land Management, Civil Engineering, or a related field; What we offer: Full-time schedule (9 hours/day, including a 1-hour paid lunch break), with a fixed shift of either 09:00-18:00 or 14:00-23:00 EEST; Fully remote work; Supportive management with no bureaucracy; Competitive compensation in USD; Opportunities for long-term professional growth. Who are we? Data is the most vital resource for next-generation spatial engineering and AI applications. Label Your Data has been providing high-quality, secure, and flexible data annotation services across various global industries since 2020. Grab your chance to join us on this innovative 3D digital twin project, and send us your CV in English highlighting your spatial and technical skills. Visit our website: https://labelyourdata.com/ *We celebrate diversity and are proud to be an equal opportunity employer.

Location: Kutaisi, Georgia; Batumi, Georgia; Rustavi, Georgia; Gori, Georgia; Poti, Georgia; Zugdidi, Georgia Do you enjoy precise, detail-oriented work and have an eye for spatial accuracy? This role puts those skills to use on a project at the intersection of geospatial data and AI. As a Data Annotator on our project, you will support building digital 3D models of power grids and other critical infrastructure. These models help energy companies analyze network conditions, predict risks, and plan maintenance using AI and physics-based simulations. You will help reconstruct electrical distribution networks in 3D by combining LiDAR point cloud data, GIS maps, and drone imagery – contributing directly to the accuracy and reliability of these digital twins. What you’ll be doing: Reconstructing 3D power grid networks using point cloud (LiDAR) and map (GIS) data; Placing 3D objects (poles, lines, conductors) to match real-world physical layouts; Aligning original 2D map data with 3D models; Labeling high-resolution drone photos to identify grid components and detect structural defects (e.g., equipment damage or wear). Requirements: Strong spatial reasoning and the ability to easily navigate 3D environments; English B1 (ability to read instructions, watch training videos, and communicate with teammates); High attention to detail, problem-solving skills, and a willingness to learn from feedback; PC/laptop with an Intel i7-11800H (or equivalent/better CPU), dedicated GPU (NVIDIA T1200 or better; RTX 4060 recommended), and 16 GB RAM minimum (32 GB preferred). Will be a plus: Any basic understanding of power grids (poles, transformers, wires) or prior experience with LiDAR data; Background in GIS, Geodesy, Cartography, Land Management, Civil Engineering, or a related field; What we offer: Full-time schedule (9 hours/day, including a 1-hour paid lunch break), with a fixed shift of either 09:00-18:00 or 14:00-23:00 EEST; Fully remote work; Supportive management with no bureaucracy; Competitive compensation in USD; Opportunities for long-term professional growth. Who are we? Data is the most vital resource for next-generation spatial engineering and AI applications. Label Your Data has been providing high-quality, secure, and flexible data annotation services across various global industries since 2020. Grab your chance to join us on this innovative 3D digital twin project, and send us your CV in English highlighting your spatial and technical skills. Visit our website: https://labelyourdata.com/ *We celebrate diversity and are proud to be an equal opportunity employer.

Location: Gyumri, Armenia; Vanadzor, Armenia; Abovyan, Armenia; Kapan, Armenia; Armavir, Armenia Do you enjoy precise, detail-oriented work and have an eye for spatial accuracy? This role puts those skills to use on a project at the intersection of geospatial data and AI. As a Data Annotator on our project, you will support building digital 3D models of power grids and other critical infrastructure. These models help energy companies analyze network conditions, predict risks, and plan maintenance using AI and physics-based simulations. You will help reconstruct electrical distribution networks in 3D by combining LiDAR point cloud data, GIS maps, and drone imagery – contributing directly to the accuracy and reliability of these digital twins. What you’ll be doing: Reconstructing 3D power grid networks using point cloud (LiDAR) and map (GIS) data; Placing 3D objects (poles, lines, conductors) to match real-world physical layouts; Aligning original 2D map data with 3D models; Labeling high-resolution drone photos to identify grid components and detect structural defects (e.g., equipment damage or wear). Requirements: Strong spatial reasoning and the ability to easily navigate 3D environments; English B1 (ability to read instructions, watch training videos, and communicate with teammates); High attention to detail, problem-solving skills, and a willingness to learn from feedback; PC/laptop with an Intel i7-11800H (or equivalent/better CPU), dedicated GPU (NVIDIA T1200 or better; RTX 4060 recommended), and 16 GB RAM minimum (32 GB preferred). Will be a plus: Any basic understanding of power grids (poles, transformers, wires) or prior experience with LiDAR data; Background in GIS, Geodesy, Cartography, Land Management, Civil Engineering, or a related field; What we offer: Full-time schedule (9 hours/day, including a 1-hour paid lunch break), with a fixed shift of either 09:00-18:00 or 14:00-23:00 EEST; Fully remote work; Supportive management with no bureaucracy; Competitive compensation in USD; Opportunities for long-term professional growth. Who are we? Data is the most vital resource for next-generation spatial engineering and AI applications. Label Your Data has been providing high-quality, secure, and flexible data annotation services across various global industries since 2020. Grab your chance to join us on this innovative 3D digital twin project, and send us your CV in English highlighting your spatial and technical skills. Visit our website: https://labelyourdata.com/ *We celebrate diversity and are proud to be an equal opportunity employer.

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: Vladivostok Workplace: onsite ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game.   For more information, visit xsolla.com.   ABOUT YOU We are looking for a Junior Developer (AI Engineering) to join the Xsolla Partner Network (XPN) team, a platform that connects game studios and publishers with content creators. The position involves participation in all stages of work on an automated content generation system: from stabilising the existing vertical video pipeline for YouTube Shorts, TikTok and Instagram Reels to developing the agentic architecture, launching the virtual AI creator direction and building analytics on the results. Working with the team means applying cutting-edge generative models and agentic tools to a real production product every day, seeing the direct effect of your work in content metrics, and learning from the inside how the games industry, the creator economy and content-driven game promotion work. The developer will work with a live system that has a real audience and measurable results, make technical decisions independently, build expertise in generative AI and take on the role of the project's technical owner as it grows. Responsibilities Take over the existing vertical video generation pipeline (script → voiceover → visuals → subtitles → editing → auto-posting → tracking links) for YouTube Shorts, TikTok and Instagram Reels, understand it from the docs and code, and bring it to stable operation. Grow the pipeline: improve content quality and virality, scale up generation volume, reduce cost and turnaround time per video. Keep track of new generation models and services (video, image, voice, LLM), test them quickly and replace outdated parts of the pipeline with better or cheaper ones. Launch and develop the virtual AI creator direction: a consistent character, voice, style and content plan. Design and improve agents: write and debug prompts and sub-agent roles, validation between phases, context and cost control. Build a dashboard for running generation and tracking content analytics (views, clicks, conversions, cost per video). Automate publishing: platform integrations, posting from mobile devices, scaling channels. Write clean, testable, documented code, including unit and integration tests. Requirements Solid Python, basic bash. Hands-on experience with LLM APIs (Claude, OpenAI, etc.) and agentic pipelines: a real project, pet project or hackathon entry you can show and talk through. Experience using Claude Code, Cursor or similar tools as a working environment, not just as autocomplete. Understanding of prompt engineering basics: defining an agent's role, limiting context, getting stable structured output. Understanding of Git, team development and Docker basics. Ability to work with REST APIs and webhooks, basic understanding of databases (SQL). Understanding of vertical content: games, creators, streams, TikToks, Shorts, how video discovery works, what shadowbans are, how mobile posting farms are set up. A big plus if this is your hobby: your own channel, editing, streaming, experiments with AI generation. Ownership: the ability to take a task end to end and deliver a result without external supervision. Initiative: your own proposals on improving the pipeline, new models and automation, and the readiness to implement them yourself. Ability to figure out someone else's system from code and documentation, reconstruct the logic and ask the right questions. Independence in technical decisions and openness in communication: flag problems immediately. Product thinking: measuring results by content metrics (views, retention, clicks) and cost per video. Ability to explain the system's capabilities and limitations to non-technical colleagues. Experimental mindset: fast hypothesis testing and the willingness to drop what did not work. Desire to grow with the project: from stabilising the current pipeline to becoming its technical owner. English at the level of reading technical documentation (Intermediate+). Nice to have Experience with video and image generation via API ( fal.ai , Kling, Runway, Seedance, Nano Banana, etc.), TTS and speech recognition (Whisper and similar). ffmpeg: assembly, normalisation, subtitles, overlays. Experience building reliable calls to paid APIs: retries, idempotency, cost tracking. n8n or other workflow tools. Telegram bots, YouTube / TikTok / Instagram / Discord APIs. Android / mobile device automation. Supabase or PostgreSQL. Experience with GCP, Docker, Kubernetes. Observability and monitoring (Datadog, OpenTelemetry). Your own channel, pet projects, open-source experience or hackathon participation. Benefits   Convenient working tools: New Mac laptop and any other necessary equipment for your efficient work. Google Workspace, Atlassian, Jira, Slack   Professional growth: Exchange of experience between employees within the company Opportunity for professional growth within the company and department Obtaining expertise in various areas and products of the company   More perks Possibility of flexibility working Access to the corporate library No dress code Comfortable and new office environment The duties and responsibilities of this position may evolve over time to support the organization’s goals and individual growth. This job description is intended to outline the general nature and level of work being performed and is not intended to be an exhaustive list of all duties, responsibilities, and qualifications required. By submitting your application, you consent to Xsolla conducting background checks, where permitted by law, after the final interview stage. All checks will comply with local regulations, and your information will be handled confidentially. Xsolla takes your privacy seriously and will not sell or externally distribute any personal data received during the hiring process. In accordance with applicable data protection laws, Xsolla is committed to protecting your personal information and respecting your privacy. For any inquiries related to data privacy, please contact: careers@xsolla.com Explore more opportunities at: https://xsolla.com/careers

— 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: United States of America What We Do: Cybercrime is growing, and more businesses are getting hit by threats that used to target only the biggest organizations. That pushes defenders like us to operate at the highest level, and it deepens our need for good people who want to make a meaningful impact. Founded in 2015 by former NSA cyber operators, Huntress is a remote-first team working to make enterprise-grade cybersecurity accessible to businesses of all sizes. We work closely with security teams and service providers protecting complex environments, often without the time or headcount to handle it all. That’s why we build our technology in-house and back it with a 24/7 human-led Security Operations Center (SOC). As a result, our platform is never disconnected from the experts who manage it, ensuring our customers' protection. Huntress now secures more than 6M endpoints and 16M identities worldwide. Those numbers keep growing because more businesses rely on us to help carry the load and operate with more confidence. Every day, you can see that commitment in how we stand with our customers and how we show up for each other. Reports to: Director, Engineering Location: Remote US, Only Compensation: $165,000 to $190,000 base plus bonus and equity What You’ll Do: Huntress is building an Agentic SOC. When our detection pipeline raises a signal, an LLM-based agent picks it up and investigates it end-to-end. It gathers telemetry across our products, reconstructs what happened, and makes a well-documented determination about whether the activity is malicious. Over time, it will take on more of the work itself, growing from resolving routine cases to acting fast when it finds an attack and handing analysts cases with the evidence already assembled. This system is meant to augment our analysts, not replace them. It takes the high-volume, repetitive work off their plates so they can focus on complex cases and hands-on keyboard intrusions where human expertise matters most. It also reduces toil in the rest of their day by using LLMs to pre-process the output of the tools analysts use constantly, so they start from a clear picture instead of raw telemetry. This isn’t a chatbot bolted onto a dashboard. The system investigates a large volume of signals a day across thousands of customer organizations. Many signals are benign, but some are live intrusions where minutes matter. The telemetry the system reads comes from environments where attackers are actively operating. Because the system makes real decisions, like closing an investigation or isolating a host, it has to be right, it has to show its work, and it has to know when to hand off to a person. As a Senior Software Engineer on the Agentic SOC team, you’ll build and ship core parts of this system. You’ll work closely with the team’s technical leads, SOC analysts, product researchers, and product managers. You’ll own significant pieces end-to-end, from an ambiguous problem to a production feature you can show is working. We make full use of AI coding tools to enable you to accelerate your development. We don’t cap token usage. We expect you to use AI and all tools responsibly. Responsibilities: Build the investigation system. You design, build, and ship the components that make agentic investigation work: the tools agents use to query telemetry, the logic that drives an investigation, and the structured, evidence-backed output that analysts and customers see. Turn analyst expertise into agent behavior. You sit with SOC analysts and product researchers to understand how they triage and investigate a given kind of Signal, then encode that into what the agent looks for, what it gathers, and how it explains its conclusions. Take toil off analysts’ plates. You build LLM-powered features that pre-process the output of tools analysts use every day. They summarize, correlate, and highlight what matters, so analysts spend their time on judgment instead of assembly. Measure what you ship. You build and extend the evaluations that tell us whether the system is getting better or worse, and you back your changes with evidence rather than a handful of good-looking examples. Build with a security mindset. The agent reads attacker-influenced data, runs across thousands of customer tenants, and can take action in customer environments. You think about how what you build could be misused or manipulated, and you design for it. Build for production. You write reliable, observable, cost-conscious code that behaves well when models are slow, wrong, or unavailable. You operate what you build and help keep the system healthy as new detections and products come online. Collaborate and raise the bar. You give thoughtful code reviews, help teammates get unstuck, share what you learn about building with LLMs, and contribute to technical discussions and design reviews with clear reasoning about tradeoffs. Balance rigor with pragmatism. You know when to prototype quickly to learn something and when to slow down because the cost of being wrong is high. What You Bring To The Team: 6+ years of professional software development experience, including building and operating production backend systems Experience building applications with LLMs, including tool use, structured output, prompt and context design, and evaluation. Experience shipping agents to production is a strong plus An understanding of how LLM-based systems fail, and good habits for testing and debugging non-deterministic behavior Solid backend fundamentals, including APIs, background jobs and queues, concurrency, relational databases such as Postgres, and data stores such as Redis Strong skills in one or more backend languages and the ability to pick up new ones quickly. Our primary stack is Ruby on Rails. Prior Rails experience isn’t required, and we expect you to become fluent in it Security awareness: you think about untrusted input, access control, and keeping one customer’s data separate from another’s Curiosity about how security analysts think and work, and a willingness to spend real time learning from them Experience with AWS, Azure, or other public cloud environments Experience with AI coding tools, such as Claude Code BS or MS in Computer Science or Engineering, or equivalent experience Bonus Points: Experience working in or building for a SOC, incident response, threat hunting, or detection engineering. It isn’t required, but it helps a lot, because we build these workflows around how our analysts actually investigate Familiarity with endpoint, identity, and Microsoft 365 telemetry and with attacker tradecraft (e.g., MITRE ATT&CK) Experience building evaluation pipelines or datasets for ML or LLM systems Experience with Ruby on Rails What We Offer: 100% remote work environment - since our founding in 2015 Generous paid time off policy, including vacation, sick time, and paid holidays 12 weeks of paid parental leave Highly competitive and comprehensive medical, dental, and vision benefits plans 401(k) with a 5% contribution regardless of employee contribution Life and Disability insurance plans Stock options for all full-time employees One-time $500 reimbursement for building/upgrading home office Annual allowance for education and professional development assistance $75 USD/month digital reimbursement Access to the BetterUp platform for coaching, personal, and professional growth #BI-REMOTE Huntress is committed to creating a culture of inclusivity where every single member of our team is valued, has a voice, and is empowered to come to work every day just as they are. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, disability, veteran status, genetic information, marital status, or any other legally protected status. We do discriminate against hackers who try to exploit businesses of all sizes. Accommodations: If you require reasonable accommodation to complete this application, interview, or pre-employment testing or participate in the employee selection process, please direct your inquiries to accommodations@huntresslabs.com . Please note that non-accommodation requests to this inbox will not receive a response. Huntress uses artificial intelligence tools to assist in reviewing and evaluating job applications, including resume screening, skills assessment, and candidate matching and comparisons. These AI tools support our human recruiters in the initial review process, but do not make final hiring decisions without human involvement. By submitting your application, you acknowledge this use of AI in our recruitment process. Please review our Candidate Privacy Notice for more details on our practices and your data privacy rights. #BI-Remote

Location: United States of America What We Do: Cybercrime is growing, and more businesses are getting hit by threats that used to target only the biggest organizations. That pushes defenders like us to operate at the highest level, and it deepens our need for good people who want to make a meaningful impact. Founded in 2015 by former NSA cyber operators, Huntress is a remote-first team working to make enterprise-grade cybersecurity accessible to businesses of all sizes. We work closely with security teams and service providers protecting complex environments, often without the time or headcount to handle it all. That’s why we build our technology in-house and back it with a 24/7 human-led Security Operations Center (SOC). As a result, our platform is never disconnected from the experts who manage it, ensuring our customers' protection. Huntress now secures more than 6M endpoints and 16M identities worldwide. Those numbers keep growing because more businesses rely on us to help carry the load and operate with more confidence. Every day, you can see that commitment in how we stand with our customers and how we show up for each other. Reports to: Director, Engineering Location: Remote US, Only Compensation: $215,000 to $240,000 base plus bonus and equity What You’ll Do: Huntress is building an Agentic SOC. When our detection pipeline raises a signal, an LLM-based agent picks it up and investigates it end-to-end. It gathers telemetry across our products, reconstructs what happened, and makes a well-documented determination about whether the activity is malicious. Over time, it will take on more of the work itself, growing from resolving routine cases to acting fast when it finds an attack and handing analysts cases with the evidence already assembled. We’re hiring a Principal Software Engineer to head this effort. This system is meant to augment our analysts, not replace them. It takes the high-volume, repetitive work off their plates so they can focus on complex cases and hands-on keyboard intrusions where human expertise matters most. It also reduces toil in the rest of their day by using LLMs to pre-process the output of the tools analysts use constantly, so they start from a clear picture instead of raw telemetry. This isn’t a chatbot bolted onto a dashboard. The system investigates a large volume of signals a day across thousands of customer organizations. Many signals are benign, but some are live intrusions where minutes matter. The telemetry the system reads comes from environments in which attackers are actively operating. Because the system makes real decisions, like closing an investigation or isolating a host, it has to be right, it has to show its work, and it has to know when to hand off to a person. As the technical lead, you’ll own the system’s architecture and direction. That means deciding how an investigation is structured, where deterministic code ends and model reasoning begins, what the agent can and can’t touch, how we know it’s working, and which decisions it makes on its own as it proves itself. You’ll work closely with SOC analysts, detection engineers, product, and other engineering teams. You’ll go deep in the code and help the engineers around you grow. Your work will directly shape how Huntress scales protection for the 99% . We make full use of AI coding tools to enable you to accelerate your development. We don’t cap token usage. We expect you to use AI and all tools responsibly. Responsibilities: Own the architecture of agentic investigation. You help define how signals move from detection into investigation, how investigation state is managed, how tools are designed and exposed to agents, and what a finished investigation contains: the verdict, the timeline, the scope, and the evidence behind every claim. When the team is stuck between options, you make the call, and the foundations you set are what others build on for years. Build agents that investigate like a strong analyst. You work alongside our SOC and product researchers to learn how experienced analysts actually triage and investigate, then turn that into agent behavior: which questions to ask, which evidence to gather, when to dig deeper, and when to stop and hand off to a human. Take toil off analysts’ plates. Beyond full investigations, you build LLM-powered pre-processing for the tools and data sources analysts rely on every day. It summarizes, correlates, and highlights what matters, so analysts spend their time on judgment instead of assembly. Bring a security mindset to the agent itself. The agent reads attacker-influenced data, runs across thousands of customer tenants, and can take action in customer environments. You design as if someone is trying to manipulate it, because someone will. Trust boundaries, tenant isolation, and auditability are part of the architecture from the start. Treat evaluation as a core part of the product. You define how we measure whether an investigation is correct, well-reasoned, and well-documented, and you make sure no prompt, model, or tool changes without evidence that it helps. Decide with data what the system does on its own. Based on measured performance, you decide where it acts autonomously, where a person reviews its work, and how that changes over time. You also recognize when a problem doesn’t need an agent at all. Build for production, not for demos. You design for reliability, latency, and cost at scale. The system keeps working when models are slow, wrong, unavailable, or quietly changed underneath you, and anyone can trace exactly why an investigation reached its conclusion or why an action was taken. Augment analysts, don’t replace them. You design the handoff between agent and analyst so that when a case reaches a person, the agent’s work makes them faster and better informed. You consider how analysts’ work changes as agents take on more of it, and how we explain agent decisions to partners and customers in a way they can trust. Prototype your way through hard problems. When the team hits something genuinely uncertain, you dig in first: derisk it, prove out the approach, then hand it off clearly. Be the engineering face of the Agentic SOC. In conversations with SOC leadership, other engineering teams, product, and executives, you represent the team’s technical perspective clearly and credibly. You drive alignment on key decisions, carry context in both directions, and protect the team from unclear scope. Balance technical rigor with pragmatism. You push back when a shortcut creates real risk, and you also push back on over-engineering when the goal is discovery. You have a bias for action and frequent feedback from analysts and customers, and you can explain your tradeoffs to engineers and non-engineers alike. Raise the floor and the ceiling. Your technical leadership is measured by how the whole team performs, not just by what you personally ship. That shows up in thoughtful code review, pairing on problems others are stuck on, and creating leverage through better patterns, tooling, and shared understanding. You partner with the engineering manager on team health, give direct feedback, and model the judgment and accountability you want the team to have. What You Bring To The Team: 15+ years of experience developing complex software products, including significant time as the technical lead on production systems Hands-on experience designing, shipping, and operating LLM-based agents in production, covering tool use, context management, structured output, guardrails, and evaluation, along with a clear-eyed understanding of how they fail A track record of building evaluation for non-deterministic systems, such as labeled datasets, offline evals, and regression gates, and of measuring quality over time rather than at launch A security mindset: experience building systems that handle untrusted input, enforce multi-tenant isolation, and produce an audit trail that holds up under scrutiny Experience building systems that make automated decisions with real consequences, and the judgment to know what to automate and what to leave to people Curiosity about how security analysts think and work, and a willingness to spend real time learning from them Deep backend expertise in distributed systems, queues, and durable workflows, and concurrency, with a track record of designing for throughput and correctness under load Strong skills in one or more backend languages and the ability to pick up new ones quickly. Our primary stack is Ruby on Rails, and we expect you to become fluent in it Experience with AWS, Azure, or other public cloud environments, and with data stores such as Postgres and Redis Experience with AI coding tools, such as Claude Code BS or MS in Computer Science or Engineering, or equivalent experience Bonus Points: Experience working in or building for a SOC, incident response, threat hunting, or detection engineering. It isn’t required, but it helps a lot, because we build these workflows around how our analysts actually investigate Familiarity with endpoint and identity telemetry and with attacker tradecraft Experience attacking or adversarially testing ML or LLM systems Experience with Ruby on Rails What We Offer: 100% remote work environment - since our founding in 2015 Generous paid time off policy, including vacation, sick time, and paid holidays 12 weeks of paid parental leave Highly competitive and comprehensive medical, dental, and vision benefits plans 401(k) with a 5% contribution regardless of employee contribution Life and Disability insurance plans Stock options for all full-time employees One-time $500 reimbursement for building/upgrading home office Annual allowance for education and professional development assistance $75 USD/month digital reimbursement Access to the BetterUp platform for coaching, personal, and professional growth Huntress is committed to creating a culture of inclusivity where every single member of our team is valued, has a voice, and is empowered to come to work every day just as they are. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, disability, veteran status, genetic information, marital status, or any other legally protected status. We do discriminate against hackers who try to exploit businesses of all sizes. Accommodations: If you require reasonable accommodation to complete this application, interview, or pre-employment testing or participate in the employee selection process, please direct your inquiries to accommodations@huntresslabs.com . Please note that non-accommodation requests to this inbox will not receive a response. Huntress uses artificial intelligence tools to assist in reviewing and evaluating job applications, including resume screening, skills assessment, and candidate matching and comparisons. These AI tools support our human recruiters in the initial review process, but do not make final hiring decisions without human involvement. By submitting your application, you acknowledge this use of AI in our recruitment process. Please review our Candidate Privacy Notice for more details on our practices and your data privacy rights. #BI-Remote

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

Location: Athens, Greece We are looking for a Senior Backend Engineer (Python) to join a technically demanding project involving data-intensive processing, system integration, and semantic technologies. You will play a key role in taking ownership of an existing codebase, stabilising it, and evolving it in line with project requirements. This role is ideal for an experienced engineer who is comfortable working with complex systems and understands data-driven architectures . What You'll Do: Analyse, understand, and take ownership of an existing Python-based backend; Refactor and enhance backend components with a focus on maintainability and performance; Implement and maintain data processing pipelines and integration logic; Collaborate closely with data/semantic engineers on RDF/SPARQL-driven workflows; Contribute to architecture reconstruction and technical documentation; Support deployment, configuration, and troubleshooting activities; Ensure code quality through reviews, testing, and best practices. Requirements 3+ years of professional experience in backend development; Strong proficiency in Python; Experience with: Apache Airflow and AWS; Data-intensive or integration-heavy systems; APIs, batch processing, and backend services; Configuration-driven systems (XML / JSON / YAML); Solid understanding of: Software architecture and design patterns; Debugging and working with legacy codebases; Experience working in complex, multi-stakeholder projects (EU or public-sector projects is a plus). Nice-to-Have: Familiarity with Semantic Web technologies (RDF, SPARQL, OWL); Experience with data modelling or knowledge-based systems; Exposure to DevOps practices (CI/CD, containerisation); Experience contributing to or maintaining technical documentation (e.g. AsciiDoc, Antora). Benefits We believe in rewarding talent and dedication. Here's what you can expect as part of our team: Competitive full-time salary; Private Health Coverage on the Company’s group program; Flexible Working Hours; Top-of-the-Line Tools; Professional Development: Benefit from language courses, specialized training, and continuous learning opportunities; Career Growth: Work with some of the most innovative and exciting specialists in the industry; Dynamic Work Environment: Thrive in a setting that offers challenging goals, autonomy, and mentoring, fostering both personal and company growth. If you want an exciting challenge, work with some of the coolest technologies, and enjoy your time doing it, then join us! Submit your detailed CV in English, quoting reference: ( SBEP/10/26 ). You may also consider all our other open vacancies by visiting the career section of our website ( www.eurodyn.com ) and follow us on Twitter (@EURODYN_Careers) and LinkedIn. EUROPEAN DYNAMICS (ED) ( www.eurodyn.com ) is a leading European Software, Information, and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Berlin, Stockholm, London, Nicosia, Valetta, Vienna, Den Haag, Hong Kong, etc.) The company employs over 1200 engineers, IT experts, and consultants (around 3% PhD, 41% MSc, and 54% BSc). We design and develop software applications using integrated, state-of-the-art technology. Our current IT projects have a value exceeding 300 million EURO. EUROPEAN DYNAMICS is a renowned supplier of IT services to European Union Institutions, international organizations, European Agencies, and national government Administrations in 40 countries and 4 continents. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, colour, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published at www.eurodyn.com/privacy . By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorize ED to process your personal data for the purposes of the company's recruitment opportunities, in line with the Policy.

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