Senior Machine Learning Engineer

GBG Plc

Senior ML Engineer developing production computer-vision models for GBG’s digital identity verification technology. Deploying, evaluating, and improving AI systems while mentoring CVML engineers in an Agile environment.

Posted 8/7/2026full-timeRemote • 🇬🇧 United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, implementing, and optimizing machine learning and computer vision models, with a strong focus on model evaluation metrics and CI/CD workflows. Proficient in mentoring junior engineers and collaborating with cross-functional teams to enhance product capabilities.

Highest-signal resume keywords

Machine Learning Model DevelopmentComputer Vision ExpertisePython ProficiencyPyTorch ExperienceCI/CD Pipeline Contribution

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningComputer VisionConvolutional Neural NetworksTransformersModel Evaluation MetricsData PreparationAlgorithm BenchmarkingAnomaly DetectionImage SegmentationObject Detection

Soft Skills

MentoringCollaborationTechnical GuidanceProblem SolvingCommunication

Tools & Technologies

OpenCVCI/CD ToolsLarge-Scale DatasetsMLOps PracticesAgile Methodologies

Industry Keywords

Supervised LearningUnsupervised LearningSemi-Supervised LearningPerformance MonitoringModel Lifecycle Management

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Design, implement, and optimize machine learning and computer vision models for product capabilities
Research, evaluate, and apply CNNs, transformers, and vision-language models
Implement and benchmark algorithms on large-scale datasets for accuracy and throughput
Fine-tune large-scale models using LoRA and QLoRA
Define, implement, and monitor evaluation metrics including precision, recall, ROC-AUC, and confusion matrices
Analyze training, test, and production data to identify performance gaps and reliability risks
Improve model accuracy, robustness, and system stability through data-driven enhancements
Support end-to-end ML workflows spanning data preparation, training, deployment, monitoring, and iteration
Contribute to CI/CD pipelines and production monitoring for reliable, reproducible, scalable model delivery
Diagnose and resolve model performance regressions and production issues
Mentor junior CVML engineers across ML project phases
Participate in design reviews, technical discussions, knowledge sharing, and Agile ceremonies
Suggest improvements to models, workflows, tools, and product features
Collaborate with engineering, product, and data stakeholders
Monitor emerging ML and computer vision trends and assess their real-world applicability

Requirements

What you’ll need

Bachelor’s degree or higher in Computer Science, Electrical Engineering, or a related field, or equivalent experience
Strong hands-on experience developing and deploying machine learning models in production environments
Advanced understanding of supervised, unsupervised, and semi-supervised learning
Expertise in classification, regression, clustering, and anomaly detection
Experience with convolutional neural networks, recurrent neural networks, and transformer-based models
Strong proficiency in Python and PyTorch
Experience with object detection, image segmentation, and representation learning
Experience with computer vision and scientific computing libraries such as OpenCV
Familiarity with model deployment, monitoring, and CI/CD workflows
Experience with large-scale datasets and performance-critical ML systems beneficial
Prior experience mentoring or technically guiding ML engineers
Exposure to production MLOps practices and model lifecycle management beneficial
Ability to balance research-driven exploration with pragmatic, production-focused execution

Benefits

Comp & perks

Equal opportunity employer committed to a diverse and inclusive workplace
Reasonable adjustments to the interview process
Benefits information available from the Talent Attraction team