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Machine Learning Engineer – Computer Vision Focus

JR United Kingdom

Slough

Hybrid

GBP 50,000 - 80,000

Full time

3 days ago
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Job summary

A technology company based in Slough is seeking a Machine Learning Engineer focused on computer vision to join their innovative team. The role involves developing cutting-edge machine learning models and collaborating in a hybrid work setup. Candidates should possess a Master’s degree and substantial experience in ML, particularly in model deployment. This position offers competitive compensation, equity options, and a comprehensive benefits package.

Benefits

Flexible Work Setup
Equity Options
Up to 34 days annual leave
Comprehensive private health cover
Regular in-person team events
Employer-supported pension scheme

Qualifications

  • 3+ years of experience deploying ML models in production.
  • Experience with cloud platforms and containerized deployments.
  • Solid grounding in computer vision and experience with large-scale data.

Responsibilities

  • Design, train, and deploy machine learning models for computer vision.
  • Collaborate with engineers to manage datasets for model training.
  • Maintain model performance and conduct troubleshooting.

Skills

Python
Machine Learning
Computer Vision
Data Handling
Collaboration

Education

Master’s degree in Computer Science or related field

Tools

TensorFlow
PyTorch
Docker
Kubernetes

Job description

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Machine Learning Engineer – Computer Vision Focus, slough

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Client:
Location:

slough, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

4

Posted:

26.06.2025

Expiry Date:

10.08.2025

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Job Description:

Job Title: Machine Learning Engineer – Computer Vision Focus

Overview:

We’re looking for a skilled Machine Learning Engineer to join a growing technology company building cutting-edge solutions for real-world automation. You’ll be part of a small, collaborative team applying computer vision to improve performance, efficiency, and user experience across multiple sectors.

This role offers the chance to work on high-impact machine learning problems, shape production-ready models, and contribute to the development of a platform that’s democratising access to AI-driven automation.

Key Responsibilities:

  • Model Development: Design, train, and deploy machine learning models for computer vision use cases such as object detection, classification, and segmentation.
  • Data Handling: Collaborate with data engineers to manage large datasets, ensuring quality data pipelines for model training and evaluation.
  • Algorithm Tuning: Optimise model performance through experimentation with architectures and hyperparameters.
  • Cross-Functional Collaboration: Work closely with engineers, product managers, and designers to integrate ML solutions into customer-facing applications.
  • Monitoring & Maintenance: Maintain model performance in production, troubleshoot issues, and roll out updates as needed.
  • Research & Innovation: Keep current with advances in ML and CV, and apply new methods to solve business problems.

Your Profile:

  • Master’s degree (or equivalent) in Computer Science, Machine Learning, or a related field.
  • 3+ years of experience deploying ML models in production.
  • Proficient in Python and ML frameworks (e.g., TensorFlow, PyTorch).
  • Experience working with cloud platforms and containerised deployments (e.g., Docker, Kubernetes).
  • Solid grounding in computer vision and experience with large-scale data.
  • Bonus: exposure to reinforcement learning methods.

What’s on Offer:

  • Flexible Work Setup: Hybrid-first approach with the option to work remotely or from our London collaboration space.
  • Equity Options: Share in the company’s long-term success.
  • Time Off: Up to 34 days annual leave including UK public holidays.
  • Health & Wellbeing: Comprehensive private health cover (including mental health, dental, optics, and travel insurance).
  • Retreats & Team Events: Regular in-person team gatherings and an annual company-wide retreat.
  • Pension Scheme: Employer-supported contribution plan.
  • Culture: Inclusive, open-minded, and team-oriented working environment.
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