Builds models that understand images and video: detection, segmentation and recognition.

Entry

Intermediate

Coding

Very High

Key skills

Computer vision / deep learningPythonPyTorch / TensorFlowOpenCV

Career overview

The Computer Vision Engineer builds models that understand visual data: object detection, segmentation, face recognition, OCR and video analysis. They work with CNNs, ViTs, OpenCV and edge deployment. The role leads to Senior ML Engineer, AI Solutions Architect or Generative AI Engineer positions.

Main responsibilities

  • Build and train machine learning models
  • Train, fine-tune and evaluate models
  • Serve model inference at scale
  • Prepare and curate training datasets
  • Build and maintain CI/CD pipelines
  • Monitor platform health, alerts and dashboards
  • Keep technical documentation up to date
  • Prepare and execute change requests in production
  • Analyse application logs to identify root causes
  • Automate recurring tasks with scripts

Technical skills

Computer vision / deep learning90%
Python88%
PyTorch / TensorFlow85%
OpenCV85%
CNN / ViT architectures85%
Data augmentation82%
Edge / optimised deployment78%
Evaluation78%

Technologies

PythonPyTorchTensorFlowOpenCVYOLODetectron2Hugging FaceTensorRTONNXCUDADockerKubernetesAWSGCPGitMLflowOpenVINORoboflowAlbumentations

Education level

Education requirements vary depending on the company, country and experience. Professional experience, certifications and technical skills can sometimes compensate for formal education.

High School / Bac

Less common

Bac+2 (2-year degree)

Less common

Bac+3 (Bachelor)

Less common

Bac+5 (Master / Engineering)

Common entry point

Experience & coding level

Experience level

Entry LevelJuniorIntermediateSeniorExpert

Coding level

No codingLowMediumHighVery High
Technical difficulty85%

Useful certifications

Certifications are never mandatory. They are one way among others to prove a skill.

  • Google Professional ML Engineer
  • AWS Machine Learning Specialty
  • NVIDIA Deep Learning Institute

Where can this career take you?

Multiple paths are possible. Click a role to open its profile.

Where can you go next?

Realistic next career moves, with compatibility and a transition roadmap for each.

Overlap: 24% · Difficulty: Medium

Skills to learn: LLM application design, RAG & agents, Prompt engineering

View roadmap

Where can you go from here?

A typical progression built from real career relationships. Click any role to open its profile.

Soft skills
  • Technical curiosity
  • Analytical thinking
  • Problem solving
  • Rigour and attention to detail
  • Clear communication
  • Sense of ownership

Continue your career exploration

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A documented transition from this role to the next.

Computer Vision EngineerGenerative AI Engineer

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