Senior Machine Learning Engineer

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GBG Plc

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1996

💼 Consulting

🛡️ Insurance

🔐 Security

Consulting • Insurance • Security

GBG Plc is a global leader in identity verification and fraud prevention solutions. The company offers a range of services including fast and accurate identity data verification, biometric authentication, and fraud prevention to help businesses onboard customers securely and with confidence. GBG serves various industries, including financial services, retail, gaming, and insurance, providing powerful insights from millions of global customer interactions. With over 30 years of experience, GBG is trusted by thousands of businesses worldwide to deliver multi-layered protection and optimize customer onboarding processes. Their solutions aim to build trust, protect businesses from fraud, and ensure smooth and secure customer transactions.

📋 Description

• 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

• 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

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