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How much do pyqt developer jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for pyqt developer in California is $52.15, according to ZipRecruiter salary data. Most workers in this role earn between $39.86 and $63.80 per hour, depending on experience, location, and employer.

What are some common challenges faced by PyQt Developers, and how can they be addressed?

PyQt Developers often encounter challenges such as optimizing GUI responsiveness, managing complex widget hierarchies, and ensuring compatibility across different operating systems. Addressing these requires a solid understanding of event-driven programming, efficient state management, and thorough testing on multiple platforms. Collaboration with UX/UI designers and backend developers is key to aligning interface design with functional requirements. By staying updated with PyQt documentation and leveraging community resources, developers can effectively troubleshoot and implement best practices in their projects.

What are the key skills and qualifications needed to thrive in the Pyqt Developer position, and why are they important?

To thrive as a PyQt Developer, you need strong proficiency in Python programming, experience with the PyQt framework, and a background in developing graphical user interfaces (GUIs). Familiarity with version control systems like Git, integrated development environments (IDEs) such as PyCharm or VS Code, and optional certification in Python or software development can be beneficial. Excellent problem-solving skills, attention to detail, and effective communication are valuable for collaborating with cross-functional teams and translating user requirements into intuitive interfaces. These skills are essential to create robust, user-friendly applications and to ensure effective teamwork in a dynamic software development environment.

What is a PyQt Developer job?

A PyQt Developer is a software developer who specializes in creating desktop applications using Python and the Qt framework through the PyQt library. They develop user interfaces (UIs) and integrate backend functionality to build cross-platform, high-performance applications. PyQt Developers often work with event-driven programming, signals and slots, and UI design tools like Qt Designer. Their role may also involve debugging, optimization, and packaging applications for deployment.

What are the most commonly searched types of Pyqt Developer jobs in California? The most popular types of Pyqt Developer jobs in California are:
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Pyqt Developer jobs near you
Computational Pathology Scientist

Computational Pathology Scientist

IT ENGAGEMENTS, INC.

South San Francisco, CA

Other

Posted 20 days ago

Job description

Greetings from IT Engagements
IT Engagements is a global staff augmentation firm providing a wide-range of talent on-demand and total workforce solutions. We have an immediate opening for the below position with one of our premium clients.
Role: Computational Pathology Scientist (Contract Role)
Location: San Francisco, CA
Interview process: 1. Virtual 2. Onsite
Description
Duties
The Translational Safety, Pathology team provides pre-clinical pathology assessments of risk. Within this group, the Digital Pathology team focuses on revolutionizing the analysis of digital histopathology slides by leveraging computational methods to enhance pathological evaluations traditionally performed solely by humans. Our objective is to integrate cutting-edge digital and computational techniques into pathology workflows and develop computational tools to support pathologist-driven identification and interpretation of findings.
We are seeking a talented image data scientist for a contract position within our Digital Pathology team. This role involves contributing to the development and application of image-processing methods and pipelines using both conventional techniques and advanced techniques, such as machine learning and deep learning. The successful candidate should be proficient with commercially available image analysis software and able to perform basic statistical analyses and data visualizations. Ideally, the candidate will also contribute to the development and implementation of new AI-powered image analysis algorithms and should have programming expertise, particularly in Python.
The role requires close collaboration with pathologists to design and execute image analysis workflows tailored to biological questions, as well as working with computational and data scientists across various departments. Strong interpersonal and communication skills, as well as a passion for interdisciplinary collaboration, are essential.
Skills:
Essential Skills:
  • Strong Programming Foundation: Demonstrated proficiency in Python and its scientific computing ecosystem, including libraries like NumPy, Pandas, Scikit-learn and OpenCV.
  • Version Control: Proficiency with version control systems, particularly Git, and experience with collaborative platforms like GitHub or GitLab.
  • Computer Vision & Image Analysis: Solid experience in both classical and modern image analysis techniques.
  • This includes traditional image processing and applying machine learning for tasks like image classification and semantic segmentation.
  • Whole-Slide Image (WSI) Handling: Hands-on experience processing and analyzing gigapixel whole-slide images, using libraries such as OpenSlide or similar tools.
  • Collaborative Mindset: A strong aptitude for iterative design, a proactive approach to receiving and incorporating frequent feedback from cross-disciplinary teams.
  • Communication Skills: Excellent interpersonal and communication skills, with a proven ability to explain complex computational concepts to pathologists and biologists.
Desirable Skills:
  • Advanced Deep Learning: Deep expertise in developing and implementing advanced deep learning models for digital pathology, including for tasks like instance segmentation.
  • High proficiency with at least one major framework such as PyTorch (experience with object detection libraries like Detectron2 is a plus), TensorFlow, or Keras.
  • High-Performance Computing (HPC): Experience using HPC environments and familiarity with job schedulers, specifically SLURM, for training models on large datasets.
  • Commercial Pathology Software: Practical experience with commercial digital pathology platforms (e.g., HALO, Visiopharm, or QuPath).
  • Workflow Orchestration: Experience building and managing data pipelines with workflow orchestration tools such as Dagster or Airflow.
  • Application Development: Experience building simple graphical user interfaces (GUIs) for research tools using Python frameworks like Tkinter or PyQt.
  • Cloud Computing: Familiarity with cloud computing services for model training and deployment, particularly Amazon Web Services (AWS EC2)
Education:
  • MS, or PhD-level scientist or Minimum years of experience: 5
Soft skills:
  1. Collaborative Mindset: A strong aptitude for iterative design, a proactive approach to receiving and incorporating frequent feedback from cross-disciplinary teams.
  2. Communication Skills: Excellent interpersonal and communication skills, with a proven ability to explain complex computational concepts to pathologists and biologists.
Hard skills
  1. Strong Programming Foundation: Demonstrated proficiency in Python and its scientific computing ecosystem, including libraries like NumPy, Pandas, Scikit-learn and OpenCV.
  2. Computer Vision & Image Analysis: Solid experience in both classical and modern image analysis techniques. This includes traditional image processing and applying machine learning for tasks like image classification and semantic segmentation.
  3. Whole-Slide Image Handling: Hands-on experience processing and analyzing gigapixel whole-slide images, using libraries such as OpenSlide or similar tools.
  4. Advanced Deep Learning: Deep expertise in developing and implementing advanced deep learning models for digital pathology, including for tasks like instance segmentation. High proficiency with at least one major framework such as PyTorch (experience with object detection libraries like Detectron2 is a plus), TensorFlow, or Keras.
  5. High-Performance Computing (HPC): Experience using HPC environments and familiarity with job schedulers, specifically SLURM, for training models on large datasets.
Thanks
Divya

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