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Computer Vision Remote information

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How much do computer vision remote jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for computer vision remote in Orange, CA is $22.27, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $24.90 per hour, depending on experience, location, and employer.

What is a Computer Vision Remote job?

A Computer Vision Remote job involves developing and implementing computer vision algorithms and models while working from a remote location. Professionals in this role work on tasks like image recognition, object detection, and video analysis using AI and machine learning. They collaborate with teams via online communication tools and use cloud platforms or local computing resources for model training. These jobs are common in industries like healthcare, robotics, and autonomous systems.

What are the key skills and qualifications needed to thrive in the Computer Vision Remote position, and why are they important?

Success as a Computer Vision Remote professional requires expertise in computer vision algorithms, image processing, programming (Python/C++), and a degree in computer science or a related field. Familiarity with popular frameworks such as OpenCV, TensorFlow, or PyTorch, and sometimes certifications in AI or data science, are typically advantageous. Strong communication, self-motivation, and problem-solving skills help remote workers collaborate effectively across distributed teams. These competencies are crucial for delivering high-quality solutions, meeting project deadlines, and excelling in a remote-first work environment.

What are some common challenges faced by remote computer vision professionals, and how are they addressed?

Remote computer vision professionals often encounter challenges such as collaborating across different time zones, accessing large datasets securely, and maintaining consistent communication with onsite teams. These challenges are typically overcome by using version control systems like Git, cloud storage solutions, and regular video meetings to stay connected and ensure alignment. Teams also rely on detailed documentation and code reviews to maintain project quality and foster knowledge sharing. By adopting these best practices, remote professionals can contribute effectively and remain engaged with their team and projects.

What are popular job titles related to Computer Vision Remote jobs in Orange, CA? For Computer Vision Remote jobs in Orange, CA, the most frequently searched job titles are:
What job categories do people searching Computer Vision Remote jobs in Orange, CA look for? The top searched job categories for Computer Vision Remote jobs in Orange, CA are:
What cities near Orange, CA are hiring for Computer Vision Remote jobs? Cities near Orange, CA with the most Computer Vision Remote job openings:
Computer Vision Remote jobs near you

Senior Machine Learning Engineer

Career Renew

Los Angeles, CA • Remote

$165K - $225K/yr

Full-time

Posted 26 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.