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Remote Point Cloud Modeling Jobs in Chicago, IL (NOW HIRING)

HirexHire

AI Cloud Engineer

Elk Grove Village, IL · Remote

$55 - $73.50/hr

Chicago, IL (Remote) Industry: E-Commerce Company Size: What They Do: Our client offers a powerful ... Experience leveraging AI technologies, including Claude or other large language models, to automate ...

HirexHire

AI Cloud Engineer

Elk Grove Village, IL · Remote

$55 - $73.50/hr

Chicago, IL (Remote) Industry: E-Commerce Company Size: What They Do: Our client offers a powerful ... Experience leveraging AI technologies, including Claude or other large language models, to automate ...

Soliant Consulting, Inc

Senior Cloud Architect

Chicago, IL · On-site +1

$65.50 - $89.50/hr

... model, mentorship program, and focus on diversity, equity, and inclusion. We offer a fully remote ... Senior Cloud Architect Qualified candidates will have hands on experience designing and deploying ...

NinjaTrader

Staff Cloud Security Engineer

Chicago, IL · On-site +1

$145K - $195K/yr

Lead threat modeling and security architecture reviews for new services and major platform changes ... We are not open to remote candidates for this role. Hybrid: For Chicago-based employees, we follow ...

VIATechnik

Senior VDC Manager

Chicago, IL · Remote

$130K - $145K/yr

This is a remote role within the United States. US work authorization is required. About VIATechnik ... cost analysis, point cloud to BIM, virtual reality, augmented reality, and other VDC/BIM ...

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Remote Point Cloud Modeling information

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$24

$64

$89

How much do remote point cloud modeling jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for remote point cloud modeling in Chicago, IL is $64.78, according to ZipRecruiter salary data. Most workers in this role earn between $55.24 and $73.80 per hour, depending on experience, location, and employer.

What is remote point cloud modeling?

Remote point cloud modeling involves creating 3D digital representations of objects or spaces using point cloud data, which is typically collected through laser scanners or photogrammetry. The 'remote' aspect means that the modeling work is performed from a location other than the site where the data was captured, often using specialized software to process and interpret the data. This technology is widely used in industries such as construction, architecture, surveying, and engineering for tasks like as-built documentation, measurement, and visualization. Remote point cloud modelers convert raw point cloud data into usable models, such as BIM or CAD files, that are valuable for planning, analysis, and project management.

What are some common challenges faced by professionals working in remote point cloud modeling, and how can they be addressed?

One common challenge in remote point cloud modeling is managing large data files, which can cause slow upload/download speeds and software lag. Ensuring a reliable internet connection and using cloud-based collaboration tools can help mitigate these issues. Additionally, clear communication with team members is crucial, as remote work can sometimes lead to misunderstandings about project specifications or deadlines. Regular virtual meetings and detailed documentation can help keep everyone aligned and projects on track.

What are the key skills and qualifications needed to thrive as a Remote Point Cloud Modeler, and why are they important?

To thrive as a Remote Point Cloud Modeler, you need expertise in 3D modeling, spatial data interpretation, and proficiency with point cloud processing, often supported by a degree in geomatics, engineering, or architecture. Familiarity with technical tools such as Autodesk ReCap, Bentley Pointools, and laser scanning equipment, as well as certifications in CAD or BIM, are typically required. Strong attention to detail, problem-solving abilities, and effective communication skills distinguish top performers in this role. These skills ensure accurate digital representations, efficient project collaboration, and high-quality deliverables critical for industries like construction, surveying, and design.
What are the most commonly searched types of Point Cloud Modeling jobs in Chicago, IL? The most popular types of Point Cloud Modeling jobs in Chicago, IL are:
What are popular job titles related to Remote Point Cloud Modeling jobs in Chicago, IL? For Remote Point Cloud Modeling jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Point Cloud Modeling jobs in Chicago, IL look for? The top searched job categories for Remote Point Cloud Modeling jobs in Chicago, IL are:
Remote Point Cloud Modeling jobs near you
Infographic showing various Remote Point Cloud Modeling job openings in Chicago, IL as of July 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $134,745 per year, or $64.8 per hour.
Remote Eventing / Messaging / Cloud-Native Integration Engineer

Remote Eventing / Messaging / Cloud-Native Integration Engineer

3B Staffing LLC

West Chicago, IL • Remote

$57 - $76/hr

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

Title: Eventing / Messaging / Cloud-Native Integration Engineer Location: Primarily Remote; Chicagoland Candidates Preferred Position Type: 6-Month Contract with Possible Extension Overview Looking for an Eventing / Messaging / Cloud-Native Integration Engineer to support our client's cloud modernization and acquisition-integration efforts. This senior-level consultant will assess asynchronous processing, messaging, streaming, serverless, and cloud-native managed-service dependencies that may materially affect application onboarding to a target cloud platform. The engineer will analyse representative producers, consumers, queues, topics, streams, event triggers, retry behaviour, dead-letter handling, ordering, replay, fanout, idempotency, and failure scenarios. This person will determine whether existing dependencies can be retained through a controlled exception, bridged to a target service, replaced with an equivalent architecture, or require deeper application refactoring. What You Bring to the Role. (Ideal Experience)
  • Senior-level experience with distributed systems, event-driven architecture, messaging platforms, and cloud-native integrations.
  • Strong experience with technologies such as:
    • Amazon SQS
    • Amazon SNS
    • Amazon Kinesis
    • RabbitMQ
    • Apache Kafka
    • Amazon MSK
    • AWS Lambda
    • Lambda event source mappings
  • Experience with HTTP-based integrations, asynchronous APIs, and event-driven integration patterns.
  • Familiarity with serverless and bring-your-own-application deployment models.
  • Deep knowledge of:
    • At-most-once, at-least-once, and effectively-once delivery patterns
    • Topic and partition design
    • Routing and fanout
    • Consumer groups
    • Message ordering
    • Deduplication
    • Visibility timeouts
    • Acknowledgment models
    • Retries and backoff strategies
    • Dead-letter queues
    • Event replay
    • Idempotency
    • Schema evolution
    • Backpressure
    • Event-trigger behavior
  • Strong understanding of operational observability for event-driven and asynchronous systems.
  • Ability to identify differences between a straightforward technology substitution and a change to application behavior or processing semantics.
  • Experience assessing platform, security, networking, deployment, and operational dependencies.
  • Ability to estimate producer, consumer, application, platform, security, testing, and support effort for multiple migration approaches.
  • Strong written communication skills with the ability to document complex architectural findings clearly and concisely.
What You'll Do. (Skills Used in this Position)
  • Assess messaging, streaming, serverless, asynchronous processing, and managed-service dependencies.
  • Analyze representative:
    • Producers and consumers
    • Queues and topics
    • Streams and partitions
    • Event triggers
    • Retry mechanisms
    • Dead-letter handling
    • Ordering requirements
    • Replay capabilities
    • Routing and fanout patterns
    • Failure behavior
  • Evaluate message-delivery guarantees, acknowledgment behavior, visibility models, consumer-group behavior, and deduplication requirements.
  • Assess idempotency, schema evolution, backpressure, event sequencing, and processing resilience.
  • Determine whether current dependencies can be:
    • Retained through a controlled exception
    • Temporarily bridged
    • Replaced with an equivalent target-platform service
    • Redesigned using a different integration pattern
    • Migrated only through application refactoring
  • Identify differences in semantics between current and proposed technologies.
  • Evaluate impacts to producers, consumers, platform services, security controls, deployment processes, and operational support.
  • Assess observability, monitoring, alerting, tracing, and failure-recovery requirements.
  • Perform bounded, non-production technical validation when needed.
  • Identify platform backlog dependencies, sequencing constraints, migration risks, and operational considerations.
  • Estimate the technical effort required for each migration path.
  • Produce concise Engineering Assessment Inputs documenting:
    • Semantic compatibility
    • Architecture implications
    • Application-refactoring requirements
    • Migration sequencing
    • Platform and security dependencies
    • Operational risks
    • Cutover and rollback considerations
    • Likely future engineering effort
  • Collaborate with application teams, integration architects, cloud platform owners, security teams, and operations stakeholders.

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