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Internship Spatial Intelligence Jobs (NOW HIRING)

KIPP

SY 26/27 Elementary STEAM Teacher

Kansas City, MO

$43K - $58K/yr

... spatial awareness to advanced mechanical engineering and block-based coding. * Visual Arts ... Guide students in mastering 21st-century technical skills (such as coding, artificial intelligence ...

JEM Group LLC

Assistant Project Manager

Camp Hill, PA · On-site

Internship, or Co-op experience as an APM or project engineer is a plus. * Site civil and/or MEP ... Basic mathematical, spatial and conceptual thinking ability. * Excellent written and verbal ...

KIPP

SY 26/27 Elementary STEAM Teacher

Kansas City, MO · On-site

$43K - $58K/yr

... spatial awareness to advanced mechanical engineering and block-based coding. * Visual Arts ... Guide students in mastering 21st-century technical skills (such as coding, artificial intelligence ...

JEM Group

Assistant Project Manager

Camp Hill, PA

Internship, or Co-op experience as an APM or project engineer is a plus. * Site civil and/or MEP ... Basic mathematical, spatial and conceptual thinking ability. * Excellent written and verbal ...

JEM Group

Assistant Project Manager

Camp Hill, PA · On-site

Internship, or Co-op experience as an APM or project engineer is a plus. * Site civil and/or MEP ... Basic mathematical, spatial and conceptual thinking ability. * Excellent written and verbal ...

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How much do internship spatial intelligence jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for internship spatial intelligence in the United States is $25.42, according to ZipRecruiter salary data. Most workers in this role earn between $20.67 and $28.85 per hour, depending on experience, location, and employer.

What is the difference between Internship Spatial Intelligence vs Spatial Data Analyst?

AspectInternship Spatial IntelligenceSpatial Data Analyst
Required CredentialsCurrently pursuing or recent graduate in GIS, geography, or related fieldBachelor's or master's in GIS, geography, data science, or related field
Work EnvironmentInternship setting, often in tech, urban planning, or environmental firmsFull-time role in data analysis, GIS, or urban planning companies
Employer & Industry UsageUsed by companies seeking entry-level GIS or spatial analysis skillsUsed by organizations analyzing spatial data for decision-making
Common Search & ComparisonInternship Spatial Intelligence vs Spatial Data Analyst

Internship Spatial Intelligence typically involves entry-level, temporary positions focused on learning GIS and spatial analysis skills, often for students or recent graduates. In contrast, a Spatial Data Analyst is a full-time professional role requiring more experience and advanced skills in analyzing and interpreting spatial data for organizational decisions.

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What cities are hiring for Internship Spatial Intelligence jobs? Cities with the most Internship Spatial Intelligence job openings:
What are the most commonly searched types of Spatial Intelligence jobs? The most popular types of Spatial Intelligence jobs are:
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Internship Spatial Intelligence jobs near you
Infographic showing various Internship Spatial Intelligence job openings in the United States as of July 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $52,867 per year, or $25.4 per hour.

AI Robotics Researcher Intern (Dexterous Manipulation)

NIO

San Jose, CA • On-site

Full-time

Re-posted 6 days ago

Job description

JOB DESCRIPTION
About NIO
NIO is a pioneer and a leading company in the premium smart electric vehicle market. Founded in November 2014, NIO's mission is to shape a joyful lifestyle. NIO aims to build a community starting with smart electric vehicles to share joy and grow together with users.
NIO designs, develops, jointly manufactures and sells premium smart electric vehicles, driving innovations in next-generation technologies in autonomous driving, digital technologies, electric powertrains and batteries. NIO differentiates itself through its continuous technological breakthroughs and innovations, such as its industry-leading battery swapping technologies, Battery as a Service, or BaaS, as well as its proprietary autonomous driving technologies and Autonomous Driving as a Service, or ADaaS.
NIO's product portfolio consists of the ES8, a six-seater smart electric flagship SUV, the ES7 (or the EL7), a mid-large five-seater smart electric SUV, the ES6, a five-seater all-round smart electric SUV, the EC7, a five-seater smart electric flagship coupe SUV, the EC6, a five-seater smart electric coupe SUV, the ET7, a smart electric flagship sedan, and the ET5, a mid-size smart electric sedan.
About the Position
We are looking for an outstanding AI Robotics Research Intern to join the team at NIO. This role operates at the cutting edge of embodied AI and dexterous manipulation, with a specific focus on utilizing large-scale foundation models and human data-based learning to empower robots with physical world intelligence.
As an intern, you will tackle the fundamental challenges of dexterous manipulation by harvesting human-object interaction data from diverse sources-ranging from unstructured web videos to high-fidelity human glove-collected data. Your work will involve translating these rich human insights into executable robotic behaviors, bridging the gap between human dexterity and machine execution. You will be responsible for deploying these policies on real hardware, to perform complex, contact-rich tasks in real-world environments
Project Scope
  • Learning from Human Demonstrations: Develop and refine scalable frameworks for the transfer of human-object interaction skills to diverse robotic embodiments.
  • Large-Scale Data Synthesis: Architect autonomous pipelines to process vast amounts of visual data and human glove-collected data, extracting the spatial and contact-rich information necessary for generalist robot training.
  • GenerativeEmbodied AI: Implement state-of-the-art generative architectures to synthesize physically grounded, high-fidelity trajectories based on human reference motions.
  • Unified Policy Training: Explore cross-embodiment representations that enable joint training on human and robot data to improve generalization in unstructured environments.
  • Sim-to-Real Deployment: Research and optimize distillation and retargeting techniques to bridge the gap between simulation-trained policies and physical robotic deployment.
  • Semantic Scene Understanding: Utilize vision-language foundation models to autonomously segment skills and extract task-relevant parameters from complex human activities.
Deliverables (End of Internship)
  • A robust pipeline for converting human multi-modal data into actionable robot motor skills.
  • A successful sim-to-real validation of a dexterous manipulation policy on a physical humanoid or multi-fingered platform.
  • A high-quality technical manuscript or demo suitable for internal review or submission to a top-tier robotics conference.

Qualifications
  • Master's or Ph.D. in Robotics, Computer Science, Artificial Intelligence, Mechanical/Electrical Engineering, or related fields.
  • Strong technical foundation in robot learning and control, including areas such as reinforcement learning, imitation learning, world modeling, or representation learning for agent-environment interactions.
  • Practical experience implementing and fine-tuning Generative Models and Transformer architectures.
  • Hands-on experience with robotic manipulation systems, particularly involving contact-rich interaction, grasping, or multi-sensor perception (e.g., tactile, force/torque, proprioception).
  • Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX, TensorFlow), with experience using robotics middleware or simulation tools (e.g., ROS/ROS2, MuJoCo, Isaac Sim, PyBullet).
  • Demonstrated ability to implement, experiment, and iterate on research ideas, including evaluating methods through empirical results on simulated or physical robotic systems.
  • Strong analytical and system-building skills, with the ability to work across simulation, learning, perception, control, and real robot deployment as part of a larger technical team.

Preferred Qualifications
  • Ph.D. (or Ph.D. candidate expecting graduation within 6-12 months).
  • Prior experience with dexterous manipulation, multi-finger robotic hands, in-hand manipulation, or grasp optimization beyond parallel-jaw grasping.
  • Experience deploying learning-based policies on real robotic hardware, including exposure to sim-to-real transfer challenges such as contact mismatch, compliance, sensing noise, or latency.
  • Familiarity with contact modeling, tactile sensing, force/torque feedback, or low-level control interfaces for manipulation.
  • Background in 3D perception, geometric representations, or learned representations relevant to physical interaction.
  • Experience with reinforcement learning in continuous control, model-based methods, or real-time policy execution.
  • A strong interest in building robust, real-world robotic systems, and motivation to see research ideas validated through physical experiments rather than simulation alone.
  • Track record of publications in top AI or robotics conferences (CoRL, ICRA, IROS, RSS, NeurIPS, CVPR, ICML).

Compensation:
The US base salary range for this full-time position is $38.00 - $46.00.
  • Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
  • Please note that the compensation details listed in US role postings reflect the base salary only. It does not include discretionary bonus, equity, or benefits.

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