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image developer

title: Key Responsibilities and Required Skills for Image Developer
salary: $80,000 - $120,000
categories: [Image Processing, Software Engineering, Computer Vision]
description: A detailed job description for an Image Developer role.

🎯 Role Definition

The Image Developer is an innovative software engineering role focused on designing, developing and maintaining high‑performance image processing and computer vision applications. This role involves building algorithms, integrating imaging systems, optimising performance, collaborating with cross‑functional teams (data science, product, hardware) and delivering scalable, production‑ready solutions that transform visual data into actionable results.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Software Engineer – Imaging or Computer Vision
  • Image Processing Engineer
  • Research Associate in Computer Vision / Machine Learning

Advancement To:

  • Senior Image Developer / Lead Image Engineering
  • Principal Computer Vision Engineer or Engineering Manager – Imaging Products
  • Director of Imaging Systems or Head of Computer Vision & Image Analytics

Lateral Moves:

  • Machine Learning Engineer – Computer Vision
  • Augmented Reality (AR) / Virtual Reality (VR) Systems Developer
  • Computational Photography Research Engineer

Core Responsibilities

Primary Functions

  1. Design, develop and deploy image processing pipelines for tasks such as image enhancement, segmentation, feature detection, object recognition and classification in diverse environments.
  2. Implement algorithms and workflows for image acquisition, preprocessing, augmentation, noise reduction, distortion correction and format conversion to support downstream applications.
  3. Integrate image‑based modules into software platforms, collaborate with product and hardware teams to ensure seamless functioning of camera, sensor or imaging subsystems.
  4. Optimize code and pipelines for performance and scalability: minimise latency, manage memory, parallelise tasks, deploy on GPU/CPU architectures or edge devices as needed.
  5. Build and maintain machine learning and deep learning‑based vision models (CNNs, transformer‑based vision architectures) for classification, segmentation, tracking or anomaly detection in image datasets.
  6. Collaborate with data scientists to label, curate and maintain large image datasets, develop annotation tools, apply transfer learning and fine‑tune models for domain‑specific imaging tasks.
  7. Conduct rigorous testing and validation of image processing applications: create unit/integration tests, perform quality assurance, debug visual artifacts, validate across devices and conditions.
  8. Monitor and evaluate model performance: compute metrics (accuracy, precision, recall, IoU, F1), identify drift, maintain dataset integrity and enhance models accordingly.
  9. Develop APIs, microservices or SDKs exposing image processing capabilities to downstream applications including web, mobile or backend services.
  10. Work with product, UX and design teams to prototype and deliver visual features, interactive image tools or imaging‑centred UIs that enhance user experiences.
  11. Stay current with emerging imaging technologies, computer vision research, libraries (OpenCV, TensorFlow, PyTorch), and propose innovation opportunities for image‑based solutions.
  12. Ensure compliance with image data governance, privacy standards, regulatory requirements (e.g., GDPR for visual data), and manage secure storage and lifecycle of imaging assets.
  13. Document architecture, code standards, algorithm descriptions and image processing workflows to support reproducibility, maintenance and onboarding of new team members.
  14. Manage version control, branch workflows, release management and continuous integration/continuous deployment (CI/CD) for image processing codebases.
  15. Liaise with hardware and sensor teams to define imaging specifications, calibrate cameras or sensors, manage firmware interactions and implement image capture protocols.
  16. Participate in cross‑functional projects such as AR/VR imaging, augmented photography, 3D reconstruction from image data, or advanced imaging sensor integration.
  17. Support production operations: monitor image pipelines in production, log and troubleshoot issues, implement fixes or upgrades and ensure availability of imaging services.
  18. Lead optimisation of visual pipelines for mobile or embedded platforms: manage constraints around memory, processing power or battery life and adapt algorithms accordingly.
  19. Mentor junior developers or interns specialised in image processing: review code, share best practices, support growth of imaging team competencies.
  20. Continuously measure and improve impact of image‑based solutions: track business KPIs tied to imaging capabilities, recommend enhancements and drive adoption of imaging features.

Secondary Functions

  • Support ad‑hoc data requests and exploratory analysis on image datasets or imaging pipeline metrics.
  • Contribute to the organisation’s imaging roadmap and strategy by aligning imaging capabilities with business goals and product features.
  • Collaborate with business units to translate user or product requirements into engineering specifications for imaging applications.
  • Participate in sprint planning, agile ceremonies and cross‑team coordination sessions focused on imaging or computer‑vision projects.

Required Skills & Competencies

Hard Skills (Technical)

  • Proficiency in programming languages such as Python, C++ or Java for building image processing and computer vision applications.
  • Deep knowledge of image processing libraries and frameworks (OpenCV, PIL, scikit‑image, TensorFlow, PyTorch) and experience implementing vision algorithms.
  • Experience with machine learning/deep learning frameworks and techniques for image data: CNNs, segmentation models, object detection, transfer learning.
  • Strong understanding of image formats, compression, color spaces, transformations (scaling, rotation, registration), noise reduction and camera calibration.
  • Demonstrated experience designing and optimising pipelines for performance, scalability and real‑time/edge deployment of image processing.
  • Familiarity with data annotation, dataset curation, training and evaluation workflows for image‑based machine learning.
  • Knowledge of software engineering best practices: version control (Git), CI/CD, modular architecture, code review and documentation.
  • Experience integrating imaging modules with backend services, microservices or APIs, including deployment to cloud or edge environments.
  • Understanding of sensor/hardware, imaging devices, camera specifications, firmware, calibration workflows or embedded imaging systems.
  • Ability to measure and analyse image pipeline performance, define KPIs, interpret results, handle drift detection and drive continuous improvement.

Soft Skills

  • Excellent problem‑solving and analytical thinking: ability to dissect complex imaging challenges, propose effective algorithmic solutions and implement them.
  • Strong communication skills: able to collaborate with multi‑disciplinary teams (data science, product, hardware), explain technical imaging concepts to non‑technical stakeholders.
  • Attention to detail and quality‑focus: ensure robustness of image pipelines, accuracy of results and reliability of visual applications.
  • Adaptability and learning orientation: keep up‑to‑date with evolving imaging, computer‑vision and machine‑learning trends and integrate new approaches.
  • Time‑management and prioritisation: manage multiple image‑processing tasks, projects and deadlines efficiently in a dynamic environment.
  • Leadership and mentoring: guide junior team members, share knowledge, review code and build capacity in imaging development.
  • Collaboration and teamwork: work effectively across functions, contribute to shared goals and foster a positive inclusive team culture.
  • Creativity and innovation: apply inventive approaches to imaging problems, prototype novel features and contribute to product differentiation via visual capabilities.
  • Strategic mindset: align imaging development with product/business objectives, identify high‑impact opportunities and measure outcomes.
  • Integrity and accountability: assume ownership of imaging modules, maintain data and code confidentiality, and deliver high‑standards reliably.

Education & Experience

Educational Background

Minimum Education:
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics or a related technical field.
Preferred Education:
Master’s degree or higher in Computer Vision, Robotics, Machine Learning or Imaging Science.
Relevant Fields of Study:

  • Computer Science / Software Engineering
  • Computer Vision / Imaging Science
  • Electrical Engineering
  • Applied Mathematics / Data Science

Experience Requirements

Typical Experience Range:
3–5 years of experience in image processing, computer vision or software development in imaging applications.
Preferred:
5+ years of experience developing and deploying image processing applications, leading imaging projects, mentoring others and delivering production‑ready vision solutions.

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