{"id":2053750,"url":"https://alion.io/job/niantic-spatial-ai-engineer-computer-vision","title":"AI Engineer, Computer Vision","company":{"id":171874,"name":"Niantic Spatial","domain":"nianticspatial.com","url":"https://alion.io/company/niantic-spatial","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":165600,"max":221000,"currency":"USD","period":"year","gross":null,"usd_annual":221000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Localization","optional":false},{"name":"Physical AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"SLAM","optional":false},{"name":"Core ML","optional":true},{"name":"Digital Twin","optional":true},{"name":"Fine-tuning","optional":true},{"name":"ONNX","optional":true},{"name":"Self-Supervised Learning","optional":true},{"name":"TensorRT","optional":true},{"name":"World Models","optional":true}],"status":"live","first_seen_at":"2026-10-07T22:11:57Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-12T05:22:12Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"About Niantic Spatial\nAt 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.\nOur reconstruction technology captures environments with geometric accuracy and extreme detail from any standard camera, and our Visual Positioning System delivers precise positioning almost anywhere in the world. We serve customers across robotics, the public sector, and energy and industrial markets - building for the 80% of economic activity that takes place beyond our screens.\nAbout the Team\nLocalization 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.\nThat 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.\nAbout the Role\nWe'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.\nThis 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.\nWhat You'll Do\nTrain 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.\n\nBuild 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.\n\nRun 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.\n\nExtend 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.\n\nSupport 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.\n\nBridge 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.\n\nWhat You'll Bring\nExperience training deep learning models for computer vision tasks in PyTorch - through coursework, research, internships, or early industry work.\n\nFoundational 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).\n\nComfort working with large image or 3D datasets - preprocessing, curation, and understanding how data quality affects model behavior.\n\nFamiliarity 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.\n\nStrong Python skills and a habit of writing code that others can rerun and build on.\n\nA bachelor's or master's degree in computer science, computer vision, robotics, or a related field, or equivalent practical experience.\n\nNice to Have\nPublished or contributed to work on learned localization, visual place recognition, scene-coordinate regression, or vision foundation models (CVPR, ECCV, ICCV, NeurIPS, 3DV, or equivalent).\n\nExperience with large-scale self-supervised or multi-view pretraining, or fine-tuning vision foundation models for geometric tasks.\n\nExposure to inference optimization for edge or mobile hardware (TensorRT, ONNX, CoreML, or similar).\n\nExperience with petabyte-scale spatial data: point clouds, meshes, posed image collections, or geospatial indexing.\n\nBackground in robotics, augmented reality, 3D reconstruction, digital twins, or autonomous systems.\n\nPrior industry or research internship experience shipping or contributing to a production CV system.\n\nCompensation & Benefits\nThe 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.\nLocation & Work Model\nThis role is based in our San Francisco, CA office on a hybrid schedule with a minimum of 3 days per week in office.\nInclusive Application\nWe 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.\nEqual Opportunity\nNiantic 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.\nCandidate Privacy\nI 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.","description_format":"text","description_chars":7072,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Robotic Software & Control Systems","Space & Aerospace","Earth Observation","Industrial IoT (IIoT)"],"lifecycle":[{"event":"open","at":"2026-10-07T22:43:06Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 9","filings_12m":9,"filings_prev_12m":0,"green_card_filings_12m":0,"median_offered_wage_usd":172500,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":8}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":4,"expected_fill_days":60,"reasons":["conf:1","velocity","win:early"],"computed_at":"2026-10-12T06:55:09Z"},"pay":{"stated_usd_annual":221000,"is_top_pay":false},"html_url":"https://alion.io/job/niantic-spatial-ai-engineer-computer-vision","json_url":"https://alion.io/job/niantic-spatial-ai-engineer-computer-vision.json","meta":{"generated_at":"2026-10-12T09:08:34Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":13710,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-13T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":171874},"rest":"https://alion.io/mcp/rest/get_company?id=171874"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fniantic-spatial-ai-engineer-computer-vision"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fniantic-spatial-ai-engineer-computer-vision"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fniantic-spatial-ai-engineer-computer-vision"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/niantic-spatial-ai-engineer-computer-vision\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fniantic-spatial-ai-engineer-computer-vision"}]}