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Full Time Spatial Reasoning Jobs (NOW HIRING)

IntelliPro

Data Annotator

San Francisco, CA · On-site

Required : • Proven proficiency in LiDAR or Point Cloud systems, or alternatively, a relevant undergraduate degree demonstrating superior 3D spatial reasoning. • Requires full-time physical ...

ROTATEK

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Mechanical Engineer - Laser Tracker and Scanner Operator

Mahwah, NJ · On-site

$70K - $125K/yr

Strong mechanical aptitude and spatial reasoning ability * Willingness to travel (typically 40%-60 ... Job Type: Full-time Benefits: * 401(k) * Dental Insurance * Health Insurance * Life Insurance

Ranger Die, Inc.

Tool & Die Designer

Coopersville, MI · On-site

$23.95 - $36.80/hr

... spatial reasoning; technical drawing skills; problem-solving; sound judgment in decision making ... package for eligible full time employees that includes medical, dental, vision, life, and ...

Ranger Die, Inc.

Tool & Die Designer

Coopersville, MI · On-site

$23.95 - $36.80/hr

... spatial reasoning; technical drawing skills; problem-solving; sound judgment in decision making ... package for eligible full time employees that includes medical, dental, vision, life, and ...

Higharc

Research Engineer

Design and conduct original research in spatial reasoning for residential construction, developing ... S based employees that are full-time. You'll also have access to other big-company benefits such ...

TAS Environmental Services LP

Welder

Orange, TX · On-site

$18.50 - $24.50/hr

Job Type Full-time Description DESCRIPTION: TAS Environmental Services, LP is recognized as a ... Welders need to be able to read blueprints, understand spatial reasoning, and interpret 2D and 3D ...

TAS Environmental Services

Welder

Orange, TX · On-site

$18.50 - $24.50/hr

The following list of benefits is offered only to employees in regular (full-time) positions ... Welders need to be able to read blueprints, understand spatial reasoning, and interpret 2D and 3D ...

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All JobsFull Time Spatial Reasoning Jobs

Full Time Spatial Reasoning information

See salary details

$100.5K

$123.1K

$153K

How much do full time spatial reasoning jobs pay per year?

As of Jun 19, 2026, the average yearly pay for full time spatial reasoning 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 the difference between Full Time Spatial Reasoning vs Full Time Geospatial Analyst?

AspectFull Time Spatial ReasoningFull Time Geospatial Analyst
Required CredentialsBachelor's in Geography, GIS, or related field; often certifications in spatial analysisBachelor's in Geography, GIS, or related field; certifications in GIS software
Work EnvironmentDesigning spatial models, analyzing spatial data, often in research or planning settingsCreating maps, analyzing geospatial data, supporting projects in government or private sectors
Industry UsageAcademic, research, urban planning, GIS developmentGovernment agencies, environmental firms, urban planning, GIS service providers

Full Time Spatial Reasoning focuses on analyzing and interpreting spatial data to develop models and solutions, often in research or planning contexts. Full Time Geospatial Analysts primarily create maps and analyze geospatial data to support projects in various industries. While both roles require similar educational backgrounds, their daily tasks and industry applications differ.

More about Full Time Spatial Reasoning jobs
What are the most commonly searched types of Spatial Reasoning jobs? The most popular types of Spatial Reasoning jobs are:
What job categories do people searching Full Time Spatial Reasoning jobs look for? The top searched job categories for Full Time Spatial Reasoning jobs are:
Full Time Spatial Reasoning jobs near you
Infographic showing various Full Time Spatial Reasoning job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $123,139 per year, or $59.2 per hour.
Machine Learning Engineer - Geospatial (TS/SCI)

Machine Learning Engineer - Geospatial (TS/SCI)

LaunchCode

Springfield, VA • On-site

$175K - $250K/yr

Full-time

Posted 17 days ago

Job description

Description
Title: AI/Machine Learning Engineer - Vision Language Models / Multimodal AI (NGA)
Location: Springfield or Herndon, VA (onsite)
Clearance: TS/SCI (CI Poly preferred)
Position Type: Full-Time, Direct Hire
Pay: $175,000 to $250,000 for an SME
Company: The name of our partner organization will be disclosed during the interview process. This is not a direct role with LaunchCode; it is a position through LaunchCode, working with one of our partner companies.
Disclaimer: We are unable to provide work sponsorship for this role
Overview:
We're hiring a AI/Machine Learning Engineer with strong experience in multimodal AI and large-scale model training to support advanced vision-language initiatives in a secure government environment. This role will focus on fine-tuning Vision Language Models (VLMs) on domain-specific geospatial imagery, building scalable AWS training infrastructure, and developing evaluation frameworks for image understanding and spatial reasoning. Ideal candidates will have deep experience with PyTorch, HuggingFace, distributed training, and computer vision, along with the ability to optimize and deploy multimodal models in mission-critical environments.
Huge plus for candidates who have hands-on experience taking multimodal models such as CLIP, LLaVA, Qwen-VL, or similar Vision Language Models and fine-tuning them on classified or mission-specific imagery datasets. The ideal candidate can build the AWS infrastructure needed to train and scale these models, evaluate performance improvements across real-world use cases, and deploy solutions into secure government or air-gapped environments.
Key Responsibilities:
  • Design and execute fine-tuning pipelines for Vision Language Models (VLMs) using domain-specific imagery datasets
  • Handle data preprocessing, training orchestration, and hyperparameter optimization for multimodal models
  • Build evaluation frameworks for image understanding, visual question answering, and spatial reasoning tasks
  • Develop scalable AWS-based ML infrastructure using SageMaker and GPU-enabled EC2 for distributed training
  • Create data pipelines for curating, annotating, and transforming geospatial imagery into model-ready datasets
  • Partner with applied scientists and architects on model architecture improvements, LoRA/QLoRA strategies, and inference optimization

Required Qualifications:
  • Active TS/SCI with CI Poly
  • 5+ years of machine learning engineering experience focused on deep learning
  • 1+ year of hands-on experience fine-tuning foundation models (LLMs or VLMs)
  • Experience with LoRA, QLoRA, adapters, supervised fine-tuning, instruction tuning, and RLHF/DPO
  • 4+ years of advanced Python development for ML workloads
  • Strong PyTorch and HuggingFace experience (Transformers, PEFT, Datasets, Accelerate)
  • Experience with distributed training frameworks such as DeepSpeed, FSDP, or Megatron
  • 3+ years working with computer vision or multimodal models
  • Familiarity with vision transformer architectures (ViT, CLIP, LLaVA, etc.)
  • Experience processing and augmenting image datasets at scale
  • 3+ years with AWS ML infrastructure including SageMaker, EC2 GPU environments, and S3
  • Experience with ML evaluation pipelines, benchmarking, metrics, and result analysis
  • Strong software engineering fundamentals including version control, testing, and CI/CD

Preferred Qualifications:
  • 2+ years working with geospatial or remote sensing imagery
  • Experience with EO or SAR satellite imagery
  • Understanding of geospatial metadata, coordinate systems, and imagery preprocessing
  • Experience with model quantization / inference optimization (vLLM, TensorRT, ONNX)
  • MLOps tooling experience (MLflow, Weights & Biases, SageMaker Experiments)
  • Familiarity with annotation tools and active learning workflows
  • Containerized ML experience with Docker / ECR / ECS / EKS
  • Experience supporting ATO processes and NIST 800-53 compliance
  • Experience deploying in air-gapped/disconnected environments
  • Familiarity with multimodal evaluation benchmarks (MMMU, MMBench, GQA)
  • Publications or contributions in computer vision, multimodal AI, or VLMs
  • Synthetic data generation experience for training augmentation

Apply