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Machine Learning Engineer (ML And Computer Vision)

Machine Learning Engineer (Computer Vision)

Location: Bristol (hybrid)

Type: Permanent (full-time)

Team: AI / Computer Vision

Visa: Unfortunately, visa sponsorship is not available for this role.

About the Company

A UK-based technology business building AI-led vision systems that turn image and video streams into automated, real-time insight. Our products are used in operational environments where speed, reliability, and accurate detection matter – helping teams monitor large areas and respond quickly when something changes.

The Role

We're looking for a Machine Learning / Computer Vision Engineer to help tackle challenging real-world problems using modern deep learning. You'll work closely with a multidisciplinary team to develop, productionise, and deploy computer vision models that run reliably across cloud and edge environments.

What You'll Be Doing

  • Build, test, and improve production-grade deep learning models for computer vision tasks (classification, detection, segmentation, tracking).
  • Optimise and deploy CV/ML pipelines to cloud and edge platforms.
  • Design, curate, and manage image/video datasets for training and evaluation.
  • Develop and maintain annotation workflows and tooling.
  • Create synthetic data pipelines (including generative approaches) to augment real-world datasets.
  • Stay current with emerging tools, methods, and best practices in CV/ML.

What We're Looking For

  • Degree in Computer Science, Electrical Engineering, Robotics (or similar), or equivalent commercial experience.
  • Proven experience delivering deep learning solutions for core CV tasks (classification / detection / segmentation / tracking).
  • Strong skills with PyTorch (or similar) and CV libraries such as OpenCV / scikit-image.
  • Strong, production-ready Python engineering (version control, testing, code reviews).
  • Analytical mindset with strong problem-solving ability.
  • Clear communicator who works well in a collaborative team.

Nice to Have

  • Experience with real-world sensor data (e.g., RGB-D, thermal, radar).
  • Model optimisation/deployment tooling (ONNX, TensorRT).
  • Edge deployment experience (e.g., NVIDIA Jetson or other resource-constrained devices).
  • Familiarity with MLOps tooling (e.g., DVC, MLflow).
  • Relevant open-source contributions in computer vision.

Interested?

If this sounds like you, apply with your CV or get in touch to discuss the role in confidence.


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