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Spatial Ai Jobs (NOW HIRING)

AI Engineer

Manhattan, NY · On-site

$100 - $125/hr

S. and have early traction combining AI, spatial computing, and video intelligence . We've just scratched the surface of what's possible with spatial video , LIDAR , and computer vision . Now we're ...

AI Engineer

San Francisco, CA · On-site

$100 - $125/hr

S. and have early traction combining AI, spatial computing, and video intelligence . We've just scratched the surface of what's possible with spatial video , LIDAR , and computer vision . Now we're ...

Cupix is building the Spatial AI platform that turns real-world environments into living, navigable environments for AEC and other industries. As we expand globally and reposition the company for ...

We're building the data stack for Physical AI. The Rerun SDK viewer is loved by some of the best robotics and spatial AI teams in the world, and Rerun Hub is live in private preview managing ...

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Spatial Ai information

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$100.5K

$123.1K

$153K

How much do spatial ai jobs pay per year?

As of Sep 9, 2026, the average yearly pay for spatial ai in the United States is $123,139.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $128,000.00 per year, depending on experience, location, and employer.

What is Spatial AI?

Spatial AI refers to artificial intelligence systems designed to perceive, understand, and interact with the physical world in real time by processing spatial data. It combines elements of computer vision, 3D mapping, and sensor fusion to enable machines to interpret and respond to their environment, commonly used in robotics, augmented reality, and autonomous vehicles. Spatial AI technologies help machines understand objects, spaces, and movement, allowing for more advanced navigation and interaction within complex environments.

How does a spatial AI specialist typically collaborate with cross-functional teams on large-scale projects?

Spatial AI specialists often work closely with data scientists, software engineers, and domain experts to develop and deploy intelligent spatial solutions. Their role involves integrating geospatial data with machine learning models, requiring frequent communication to align on project objectives, data requirements, and deployment strategies. Collaboration is key, especially when interpreting spatial data outputs for non-technical stakeholders and adapting models based on feedback from end users. Strong teamwork skills help ensure that spatial insights are actionable and support broader organizational goals.

What are the key skills and qualifications needed to thrive as a spatial AI engineer, and why are they important?

To excel as a Spatial AI Engineer, you need a solid background in computer vision, machine learning, and spatial data analysis, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools such as Python, TensorFlow, OpenCV, GIS software, and experience with 3D data processing are commonly required, along with relevant certifications in AI or spatial technologies. Creative problem-solving, strong analytical thinking, and effective communication are crucial soft skills that help bridge technical solutions and real-world applications. These skills enable the development of innovative AI-driven spatial solutions that are accurate, efficient, and effectively meet organizational or client needs.

What is the difference between Spatial Ai vs GIS Analyst?

AspectSpatial AiGIS Analyst
Required CredentialsTypically requires knowledge of AI, machine learning, and spatial data processingRequires degree in geography, GIS, or related field; certifications like GISP are common
Work EnvironmentTech-focused, often in software development or data science teamsGovernment agencies, environmental firms, urban planning departments
Industry UsageEmerging in industries leveraging AI for spatial data analysisEstablished in mapping, urban planning, environmental management
Search & Comparison IntentUnderstanding AI-driven spatial analysis rolesTraditional GIS data analysis and mapping roles

Spatial Ai focuses on applying artificial intelligence to spatial data, often involving machine learning and advanced algorithms. GIS Analysts primarily work with geographic information systems to analyze and visualize spatial data. While both roles handle spatial data, Spatial Ai emphasizes AI integration, whereas GIS Analysts focus on traditional GIS tools and methods.

What jobs are available for spatial Ai?

Jobs related to spatial AI include roles such as geospatial data analyst, GIS developer, remote sensing specialist, and spatial data scientist. These positions often require skills in geographic information systems, programming, and data analysis, and may involve working with tools like ArcGIS, QGIS, or Python. Opportunities are available in industries like urban planning, environmental management, transportation, and technology companies focused on location-based services.
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Infographic showing various Spatial Ai job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 76% Full Time, 19% Part Time, and 4% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $123,139 per year, or $59.2 per hour.

Research Scientist, Spatial AI & Perception

Waltham, MA • On-site

Boston Dynamics, Inc.
Industrial Automation Equipment Manufacturing • 51 - 200 employees

$200 - $250/hr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 15 days ago


Job description

## Research Scientist, Spatial AI & PerceptionApplylocations: Waltham Office (POST)time type: Full timeposted on: Posted Yesterdayjob requisition id: R2871As a **Spatial AI Research Scientist**on the **Atlas VLA Research team**, you will build the perception and geometric reasoning systems that give Atlas a grounded 3D understanding of the world. Your work spans the full spectrum from real-time SLAM and state estimation on humanoid hardware to offline reconstruction pipelines that produce the geometric scene structure used to train and condition large VLM/VLA models.You will design real-time SLAM and perception-based state estimation that runs on Atlas, develop offline 3D reconstruction pipelines that turn teleop and robot logs into high-fidelity geometric data, and pursue research in spatial AI, grounding language and vision into 3D geometry so that learned policies can reason about space, not just pixels. You'll collaborate closely with perception, robotics, ML & system software specialists and rapidly test your work on state-of-the-art hardware.****How You Will Make an Impact:***** Design and implement real-time SLAM and perception-based state estimation for a mobile humanoid or specialized data collection devices operating in unstructured, dynamic environments* Build offline 3D reconstruction pipelines (multi-view geometry, SfM/MVS, neural reconstruction, depth/pose fusion) that generate geometric scene structure to inform and supervise large VLM/VLA training* Pioneer research integrating large VLA and VLM models with 3D spatial perception to enable semantic, language-grounded scene reasoning.* Bridge classical geometric methods and learned approaches - knowing when to use optimization-based estimation versus learned representations, and how to combine them.* Write high-quality, maintainable C++ and Python code that fits into a large production codebase.****We’re Looking For:***** PhD in Robotics, Computer Vision, Machine Learning, Computer Science, or related fields (or equivalent research experience).* Prior experience building, and deploying SLAM, visual odometry, or 3D reconstruction systems for robots or autonomous vehicles.* Strong background in one or more of the following: + Real-time SLAM, visual-inertial odometry, and state estimation + 3D reconstruction (SfM, MVS, multi-view geometry, neural/implicit reconstruction) + Probabilistic state estimation and sensor fusion (factor graphs, filtering, optimization on manifolds) + Spatial representations, grounding language/vision into 3D geometry, geometric foundation models* Solid foundation in the math underlying geometric perception (Lie groups, nonlinear optimization, multi-view geometry).* Strong analytical and debugging skills; ability to write reliable, well-structured research code in C++ and Python.****Nice to Have:***** Experience with modern ML frameworks (PyTorch, JAX) and an understanding of how perception outputs feed large-scale model training.* Experience building reconstruction or data pipelines that produce training data for large vision or VLA models.* Familiarity with VLA / large behavior models and how spatial grounding improves manipulation and long-horizon behavior.* Publications in top-tier computer vision, ML, or robotics conferences (e.g., CVPR, ICCV, ECCV, RSS, ICRA, CoRL).****Why Join Us:***** Direct access to the world’s most advanced humanoid robot: test your models on hardware quickly and often.* A collaborative, inclusive team that values diverse perspectives and identities.* The opportunity to do applied spatial perception and VLA research with real-world impact.* A mission-focused environment where your work will define the future of general-purpose humanoids.The base pay range for this position is between $177,000 to $225,000 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and a annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment. #J-18808-Ljbffr