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Remote Image Segmentation Jobs (NOW HIRING)

IaC Engineer

Fort Mill, SC · Remote

$146K/yr

... segmentation). * Build and manage Docker images and Helm charts with security-first principles--image scanning, minimal base images, secrets management, and signed artifacts. * Integrate security ...

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

Computer Vision: image classification, object detection, OCR, segmentation, deepfake detection ... Fully remote, U.S.-based * Health Benefits : Comprehensive health, dental, and vision coverage

Senior Creative Designer

Santa Monica, CA · On-site +1

$80K - $120K/yr

... different segments, adapting visual messaging for specific audiences and platforms. Image ... The company is based in Santa Monica, CA along with Remote roles. Additional highlights... Backed ...

We're a remote-friendly team of 100+ passionate builders giving e-commerce businesses superpowers ... About Photoroom Photoroom builds AI-powered image editing technology that lets anyone -- from solo ...

A remote position does not require job duties be performed within proximity of a Visa office ... Kubernetes and container platforms Container image scanning and runtime security ...

Define cloud, container, and DevSecOps security standards including image governance, runtime ... Define network and hybrid connectivity security architecture including segmentation strategies ...

Define cloud, container, and DevSecOps security standards including image governance, runtime ... Define network and hybrid connectivity security architecture including segmentation strategies ...

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Remote Image Segmentation information

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$18

$43

$70

How much do remote image segmentation jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for remote image segmentation in the United States is $43.61, according to ZipRecruiter salary data. Most workers in this role earn between $33.89 and $50.72 per hour, depending on experience, location, and employer.

What does someone in remote image segmentation do?

A typical day for a Remote Image Segmentation specialist involves reviewing image datasets, applying annotation algorithms or manually labeling images, and collaborating with team members through virtual meetings or project management platforms. You may spend significant time optimizing models, troubleshooting data inconsistencies, and documenting your progress for other team members or stakeholders. While much of the work is independent, regular communication with data scientists, project managers, and other annotators is essential to ensure that segmentation tasks meet project goals and quality standards. This structure allows for flexibility but also demands self-motivation and strong organization to handle deadlines and evolving project requirements.

What are the key skills and qualifications needed to thrive in remote image segmentation?

To thrive as a Remote Image Segmentation specialist, you need a solid background in computer vision, deep learning, and image processing, commonly supported by a degree in computer science or a related field. Familiarity with tools like Python, TensorFlow, PyTorch, and annotation platforms, as well as knowledge of relevant data labeling standards, is highly important. Attention to detail, strong problem-solving skills, and clear remote communication help drive success in collaborative projects. These abilities ensure high-quality, accurate image segmentation results and efficient teamwork in distributed environments.

What is remote image segmentation?

A Remote Image Segmentation job involves labeling or partitioning images into different regions or objects using AI tools or manual annotation. This role is crucial for training computer vision models in applications like medical imaging, autonomous vehicles, and satellite imagery analysis. Professionals in this field work remotely using specialized software to annotate images accurately. Strong attention to detail and familiarity with image processing techniques are often required.

More about Remote Image Segmentation jobs
What cities are hiring for Remote Image Segmentation jobs? Cities with the most Remote Image Segmentation job openings:
What are the most commonly searched types of Image Segmentation jobs? The most popular types of Image Segmentation jobs are:
What states have the most Remote Image Segmentation jobs? States with the most job openings for Remote Image Segmentation jobs include:
What job categories do people searching Remote Image Segmentation jobs look for? The top searched job categories for Remote Image Segmentation jobs are:
Infographic showing various Remote Image Segmentation job openings in the United States as of August 2026, with employment types broken down into 69% Full Time, 6% Part Time, and 25% Contract. Highlights an 100% Remote job distribution, with an average salary of $90,701 per year, or $43.6 per hour.

IaC Engineer

1 point system

Fort Mill, SC • Remote

$146K/yr

Contractor

Re-posted 25 days ago


Job description

Hi ,
I hope you're doing well.

I'm reaching out regarding an exciting opportunity that I believe aligns well with your background and skill set.

To move forward, could you please provide the following details along with latest copy of resume:

Work Authorization and Expiry (If any)

LinkedIn Profile URL

Current Location with Zip code

Pay Expectation on W2 (hourly)

Complete JD:

Job Title

IaC Engineer

Location

Remote

Contract 

W2

Must haves

  • Kubernetes
  • EKS
  • Terraform
  • Strong in building Terraform modules
  • Design and work on application and build infrastructure
  • DevSecOps  


SUMMARY
We are seeking an Infrastructure as Code (IaC) Security Engineer to design, build, and maintain secure, scalable, and automated infrastructure solutions that underpin our AI security development platform. This role is responsible for owning the IaC layer across our container and orchestration stack—including EKS, Docker, and Helm—ensuring that all infrastructure is provisioned securely, repeatably, and in compliance with security best practices. The ideal candidate will embed security into every phase of infrastructure automation, from Terraform modules to CI/CD pipelines, enabling the AI security team to deliver rapidly without compromising the integrity of our environments.

Key Responsibilities

  • Design, implement, and maintain secure Infrastructure as Code solutions for cloud and containerized environments supporting AI security workloads.
  • Own and manage EKS clusters, including node group configurations, networking policies, RBAC, and pod security standards to support secure AI model development and deployment.
  • Develop and maintain hardened Terraform modules, configurations, and reusable infrastructure patterns with built-in security controls (e.g., least-privilege IAM, encryption-at-rest, network segmentation).
  • Build and manage Docker images and Helm charts with security-first principles—image scanning, minimal base images, secrets management, and signed artifacts.
  • Integrate security guardrails into CI/CD pipelines, including automated policy checks (e.g.,
  • OPA/Gatekeeper, Checkov, tfsec) for infrastructure deployments.
  • Automate environment provisioning, scaling, configuration, and release processes with a focus on immutable infrastructure and drift detection.
  • Collaborate with AI security engineers, platform teams, and DevSecOps to ensure infrastructure supports threat modeling, vulnerability management, and incident response requirements.
  • Troubleshoot and remediate infrastructure security issues across Kubernetes, Terraform, CI/CD, and container platforms.
  •  Enforce infrastructure compliance with organizational security policies, regulatory frameworks (e.g., NIST, CIS Benchmarks), and operational best practices.
  •  Document secure infrastructure patterns, deployment runbooks, and automation workflows for the AI security development team.

Requirements

  • Bachelor’s degree preferred and/or equivalent relevant experience considered.
  • Strong hands-on experience designing and implementing secure Infrastructure as Code solutions in cloud and containerized environments.
  • Deep production experience managing Kubernetes, including EKS cluster administration, networking, RBAC, and workload security.
  • Strong experience with Terraform, including development of reusable modules and secure infrastructure provisioning patterns.
  • Hands-on experience building and managing Docker images and Helm charts for containerized deployments.
  • Experience integrating infrastructure automation into CI/CD pipelines with automated validation and deployment workflows.
  • Strong understanding of infrastructure security best practices, including IAM, encryption, secrets management, and network segmentation.
  • Experience troubleshooting and remediating issues across Kubernetes, Terraform, containers, and deployment pipelines.
  • Ability to collaborate effectively with engineering, platform, and DevSecOps teams in a fast-paced environment.

Preferred Qualifications

  • Experience supporting AI, ML, or security-focused platform workloads in Kubernetes-based environments.
  • Experience with AWS and cloud-native services related to container orchestration, networking, and infrastructure automation.
  • Familiarity with infrastructure security and policy enforcement tools such as OPA/Gatekeeper, Checkov, tfsec, or similar solutions.
  • Knowledge of compliance and security frameworks such as NIST, CIS Benchmarks, or related infrastructure governance standards.