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Remote Computer Imaging Jobs in California (NOW HIRING)

Tempus

Data Architect, Next Platform

Redwood City, CA · On-site +1

$150K - $200K/yr

... and imaging data-are seamlessly accessible to autonomous AI agents. Our goal is to move beyond ... Education: Bachelor's Degree in Computer Science, Health Informatics, or a related field.

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Remote Computer Imaging information

What is remote computer imaging?

Remote computer imaging is the process of installing or deploying operating systems, software, and configurations onto computers over a network without needing physical access to the devices. IT professionals use specialized tools to create standardized images of systems, which are then sent and installed remotely, often to set up multiple machines efficiently. This method is commonly used in organizations to ensure consistency, save time, and streamline the setup or reconfiguration of computers, especially for remote or distributed teams.

What are some common challenges faced by professionals in remote computer imaging, and how can they be addressed?

Remote computer imaging specialists often encounter challenges such as limited access to physical devices, network latency, and ensuring secure data transfer. To address these issues, professionals typically rely on robust remote management tools, clear communication with onsite staff, and thorough documentation of imaging procedures. Staying updated on best practices for remote deployment and troubleshooting, as well as collaborating closely with IT support teams, can help mitigate most operational hurdles.

What are the key skills and qualifications needed to thrive as a remote computer imaging specialist, and why are they important?

To thrive as a Remote Computer Imaging Specialist, you need a solid understanding of operating systems, disk imaging techniques, and network protocols, typically supported by IT certifications such as CompTIA A+ or Microsoft Certified: Modern Desktop Administrator Associate. Familiarity with imaging tools like Symantec Ghost, Microsoft Deployment Toolkit (MDT), or Clonezilla is essential for efficient system deployment and troubleshooting. Strong attention to detail, problem-solving skills, and effective remote communication are crucial soft skills for this role. These skills ensure accurate and secure deployment of computer systems, minimize downtime, and enable seamless support for distributed teams.

What is the difference between Remote Computer Imaging vs Remote Desktop Support?

AspectRemote Computer ImagingRemote Desktop Support
Primary FocusCreating and deploying system images to multiple computersAssisting users with troubleshooting and resolving issues via remote access
Required SkillsImaging software, OS deployment, hardware configurationTroubleshooting, software installation, user support
Work EnvironmentIT departments, system administrators, enterprise settingsHelp desks, IT support teams, customer service
CertificationsCompTIA A+, Microsoft Certified: Modern Desktop AdministratorCompTIA A+, Microsoft Certified: Modern Desktop Administrator

Remote Computer Imaging involves creating and deploying system images across multiple devices, focusing on setup and deployment. Remote Desktop Support centers on assisting users with technical issues through remote access, emphasizing troubleshooting and user assistance. While both roles require similar certifications and work environments, their core responsibilities differ significantly.

What are popular job titles related to Remote Computer Imaging jobs in California?

For Remote Computer Imaging jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Computer Imaging jobs in California look for?

The top searched job categories for Remote Computer Imaging jobs in California are:

What cities in California are hiring for Remote Computer Imaging jobs?

Cities in California with the most Remote Computer Imaging job openings:

Remote Computer Imaging jobs near you

Senior Machine Learning Engineer

Career Renew

Los Angeles, CA • Remote

$165K - $225K/yr

Full-time

Re-posted 5 hours ago

Job description

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus equity.
We are the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis.
Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities.

About the Role

We are seeking an experienced Senior ML Engineer to join our team who owns the representation-learning and generative modeling stack that powers Pictor’s virtual staining. The ideal candidate will have deep expertise in Machine Learning and building generalizable, production-ready models, and evaluations that stand up in clinical workflows.
Design and implement novel computer vision and deep learning algorithms for virtual staining and digital pathology applications
Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative improvements
Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative architectures for image-to-image translation tasks
Apply classical and learned image enhancement, denoising, and semantic segmentation techniques to histopathology imaging challenges
Explore image representation in latent space for efficient, high-fidelity virtual staining
Stay current with state-of-the-art research, identifying opportunities to apply novel techniques to PictorLabs’ product roadmap

Collaboration
Collaborate with ML Engineering and software teams to translate research prototypes into production-ready systems meeting latency and throughput requirements
Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and custom architectures
Partner with software engineers, data scientists, and pathology domain experts to integrate research into production systems
Contribute to best practices for data engineering, data governance, and data quality across research and production pipelines
Leverage AI coding and ideation tools to accelerate research velocity and prototype new approaches

Required Qualifications

PhD (preferred) or Master’s degree in Computer Science, Electrical Engineering, or a related field
Deep expertise in computer vision and deep learning, with hands-on experience in one or more of: Vision Transformers, Diffusion Models, GANs, semantic segmentation, or classical image enhancement and denoising
Expert proficiency in Python and PyTorch and other scientific computing environments a plus
Strong mathematical foundation in linear algebra, probability, and optimization
Experience with large-scale model training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure)
Knowledge of handling large scale image data, data version controls, model registry, has experience dealing with ML lifecycles
Experience with feature search, data balancing, and data curation pipelines.
Knowledge of software engineering best practices including version control (Git) and CI/CD pipelines
Excellent collaboration and communication skills, with the ability to work effectively in a fast-paced, cross-functional international startup environment
Extensive use of AI tools for coding, optimization, and ideation

Preferred Qualifications

Experience with medical imaging, digital pathology, or whole slide image (WSI) processing
Experience with LoRAs, transformer architecture and state of the art image to image translation models (Flux 2, Z-Image) and the Hugging face ecosystem
Background in generative models and fine-tuning of foundation models
Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton
Experience with hosting computer vision model inference on NVIDIA DGX Spark.
Understanding of FDA regulatory requirements for AI/ML in medical devices
Experience with MLOps tools (MLflow, Kubeflow) and model versioning practices
Develop tools and frameworks to streamline ML research workflows, experimentation, and reproducibility

What We Offer

The opportunity to work on technology that directly improves patient outcomes and transforms clinical diagnostics, alongside a talented team of engineers and researchers pushing the boundaries of AI in healthcare. You will have the freedom to pursue high-impact research while seeing your work deployed at scale in real clinical environments.