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Virtual Machine Jobs in Compton, CA (NOW HIRING)

Sonsoft Inc

Cloud Tech Lead

Torrance, CA · On-site

$58.25 - $77.75/hr

Azure Virtual Machines, Blob Storage, Azure SQL Database, StorSimple, Azure DNS, Virtual Network, DocumentDB, Redis Cache, Azure App Service, * Strength and background in infrastructure or HPC is ...

Sonsoft Inc

Cloud Tech Lead

Torrance, CA · On-site

$58.25 - $77.75/hr

Azure Virtual Machines, Blob Storage, Azure SQL Database, StorSimple, Azure DNS, Virtual Network, DocumentDB, Redis Cache, Azure App Service, * Strength and background in infrastructure or HPC is ...

Sonsoft Inc

Cloud Tech Lead

Torrance, CA

$58.25 - $77.75/hr

Azure Virtual Machines, Blob Storage, Azure SQL Database, StorSimple, Azure DNS, Virtual Network, DocumentDB, Redis Cache, Azure App Service, * Strength and background in infrastructure or HPC is ...

SonSoft Inc.

AWS/Cloud Infrastructure

Torrance, CA · On-site

... Virtual Machines, Blob Storage, Azure SQL Database, StorSimple, Azure DNS, Virtual Network, DocumentDB, Redis Cache, Azure App Service. • Strength and background in infrastructure or HPC is ...

Sonsoft Inc

AWS/Cloud Infrastructure

Torrance, CA · On-site

Azure Virtual Machines, Blob Storage, Azure SQL Database, StorSimple, Azure DNS, Virtual Network, DocumentDB, Redis Cache, Azure App Service, * Strength and background in infrastructure or HPC is ...

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Showing results 21-40

All JobsMachine JobsVirtual Machine JobsVirtual Machine Jobs in Compton, CA

Virtual Machine information

What are the key skills and qualifications needed to thrive as a virtual machine engineer, and why are they important?

To thrive as a Virtual Machine Engineer, you need expertise in virtualization technologies, operating systems, and system architecture, usually supported by a degree in computer science or a related field. Familiarity with platforms such as VMware, Hyper-V, KVM, and tools like vSphere or VirtualBox, along with relevant certifications like VCP or RHCE, is highly valuable. Problem-solving, attention to detail, and effective communication are crucial soft skills for managing complex environments and collaborating with IT teams. These skills ensure reliable deployment, maintenance, and optimization of virtual infrastructures, which are critical for modern business operations.

What are some common challenges faced by virtual machine administrators, and how can they be addressed?

Virtual Machine administrators often encounter challenges such as resource allocation conflicts, performance bottlenecks, and ensuring security across multiple virtual environments. Addressing these issues typically involves careful monitoring of resource usage, implementing automation for scaling, and staying up-to-date with security patches. Collaboration with network and storage teams is also essential to maintain optimal performance and prevent downtime.

What is the difference between Virtual Machine vs Cloud Engineer?

AspectVirtual MachineCloud Engineer
Required CredentialsIT certifications, virtualization knowledgeCloud platform certifications (AWS, Azure), programming skills
Work EnvironmentData centers, local servers, virtualization platformsCloud platforms, remote environments, development tools
Employer & Industry UsageIT departments, data centers, hosting providersTech companies, startups, enterprises adopting cloud solutions
Common Search & Comparison IntentUnderstanding virtualization technologyCloud infrastructure and deployment strategies

While Virtual Machines focus on creating virtualized hardware environments within physical servers, Cloud Engineers design, implement, and manage cloud-based infrastructure and services. Both roles require technical expertise, but Virtual Machines are a component used within cloud environments managed by Cloud Engineers. Understanding both helps organizations optimize their IT infrastructure effectively.

What is a virtual machine?

A virtual machine (VM) is a software-based simulation of a physical computer that runs an operating system and applications just like a real computer. VMs allow you to run multiple operating systems on a single physical machine, isolating each environment for security and flexibility. They are commonly used for software development, testing, server consolidation, and running legacy applications. Virtual machines are managed by a hypervisor, which allocates resources and ensures separation between VMs.
What are the most commonly searched types of Machine jobs in Compton, CA? The most popular types of Machine jobs in Compton, CA are:
What cities near Compton, CA are hiring for Virtual Machine jobs? Cities near Compton, CA with the most Virtual Machine job openings:
Virtual Machine jobs near you
Infographic showing various Virtual Machine job openings in Compton, CA as of August 2026, with employment types broken down into 83% Full Time, 10% Part Time, and 7% Contract. Highlights an 100% In-person job distribution.

Senior Machine Learning Engineer

Career Renew

Los Angeles, CA • Remote

$165K - $225K/yr

Full-time

Re-posted 21 days 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.