Senior Machine Learning Engineer (3968)

About GBG

Enabling safe and rewarding digital lives for genuine people everywhere

We make it our mission to ensure more genuine people have digital access to opportunities and businesses have access to more genuine people. Our technology draws on diverse and reliable data to create a single point of truth for identity and address verification.

With over 30 years of experience behind us our team and technology are focused on enabling safe and rewarding digital lives for everyone. Regardless of age location or background genuine people everywhere should be able to digitally prove who they are and where they live.

About the team and role

CVML Teams

At the heart of GBGs Documents and Biometrics portfolio our team focuses on creating unique and powerful artificial intelligence models. These models are designed to revolutionize KYC verification for our customers. We drive the development of these cutting-edge technologies aiming to provide unparalleled solutions for document verification and digital trust. Collaboration is our cornerstone as we bring together diverse expertise to achieve collective success. Guided by Agile methodology our daily operations focus on efficiency through automation.

Senior Machine Learning Engineer

The Senior Machine Learning Engineer is a senior individual contributor responsible for designing developing deploying and continuously improving machine learning and computer vision models that power productiongrade systems. This role combines strong handson technical execution with mentorship collaboration and datadriven problem solving.

Operating within an Agile environment the Senior ML Engineer works closely with the machine learning team and crossfunctional partners to translate product requirements into robust ML solutions. The role requires deep expertise in modern ML and computer vision techniques experience operating models in production and the ability to guide junior engineers through the full ML lifecycle while driving measurable improvements in model performance and product quality.

What you will do

Technical Development & Innovation

• Design implement and optimize stateoftheart machine learning and computer vision models to enhance product capabilities.
• Research evaluate and apply modern architectures and techniques including CNNs transformers and visionlanguage models.
• Implement and benchmark newly developed algorithms on largescale datasets validating both accuracy and throughput.
• Finetune largescale models using efficient adaptation techniques such as LoRA and QLoRA.

Model Evaluation & Data Analysis

• Define implement and monitor appropriate evaluation metrics (e.g. precision recall ROCAUC confusion matrices).
• Analyze training test and production data using statistical and visual techniques to identify performance gaps and reliability risks.
• Propose and implement datadriven enhancements to model accuracy robustness and system stability.

Production Deployment & MLOps

• Support endtoend ML workflows including data preparation training deployment monitoring and iterative improvement.
• Contribute to CI/CD pipelines and production monitoring to ensure reliable reproducible and scalable model delivery.
• Assist in diagnosing and resolving model performance regressions and production issues.

Mentorship & Team Contribution

• Mentor and support junior CVML engineers across all phases of ML projects including planning data collection annotation training deployment and iteration.
• Participate in design reviews technical discussions and knowledgesharing initiatives to raise overall team capability.
• Contribute actively to Agile ceremonies and collaborative problemsolving efforts.

Continuous Improvement & Collaboration

• Proactively suggest improvements to existing models workflows tools and product features.
• Collaborate effectively with engineering product and data stakeholders to deliver highimpact ML solutions.
• Maintain awareness of emerging ML and computer vision trends and assess their applicability to realworld problems.

Skills were looking for

• Bachelors degree or higher in Computer Science Electrical Engineering or a related field or equivalent experience
• Strong handson experience developing and deploying machine learning models in production environments.
• Advanced understanding of supervised unsupervised and semisupervised learning techniques.
• Expertise in classification regression clustering and anomaly detection.
• Solid experience with convolutional neural networks recurrent neural networks and transformerbased models.
• Strong proficiency in Python (C is a plus) and PyTorch (TensorFlow is a plus)
• Hands-on experience with modern neural network architectures and loss functions across tasks such as object detection image segmentation and representation learning.
• Experience using computer vision and scientific computing libraries such as OpenCV.
• Familiarity with model deployment monitoring and CI/CD workflows.
• Beneficial to have experience working with largescale datasets and performancecritical ML systems.
• Prior experience mentoring or technically guiding other ML engineers.
• Beneficial to have exposure to production MLOps practices and model lifecycle management.
• Able to balances researchdriven exploration with pragmatic productionfocused execution.

To find out more

As an equal opportunity employer we are dedicated to creating a diverse and inclusive workplace where everyone feels valued and empowered. Please inform your GBG Talent Attraction Partner if you require any reasonable adjustments to the interview process.

To chat to the Talent Attraction team and find out more about our benefits and why were a great place to work drop an email toand well be in touch. You can also find out more about careers at GBG and check out our current opportunities at your potential and be part of our mission to power safe and rewarding digital lives.

Required Experience:

Senior IC