Director of Machine Learning

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.

CVML Teams

At the heart of GBG's 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.

Director – Machine Learning

The Director of Machine Learning provides strategic, technical, and people leadership for machine learning initiatives across the Documents & Biometrics organization. This role is accountable for defining the long‑term AI/ML vision and roadmap, translating business and product strategy into impactful ML capabilities, and ensuring the reliable, ethical, and scalable delivery of ML models into production.

The Director operates as both a senior technical authority and an organizational leader, driving innovation, mentoring teams, influencing stakeholders, and ensuring that machine learning efforts deliver measurable customer and business value. This role requires deep expertise in machine learning and computer vision, strong leadership capability, and the ability to operate effectively across product, engineering, operations, compliance, and executive leadership functions.

Strategic Leadership & Vision

• Define, own, and execute the long‑term AI and Machine Learning strategy for the Documents & Biometrics domain, aligned with company objectives and product roadmaps.
• Identify opportunities where machine learning can materially improve classification, extraction, fraud detection, image processing, and overall product performance.
• Serve as a thought leader for AI/ML within the organization, advocating for modern approaches, emerging technologies, and best practices.

Technical & Delivery Leadership

• Provide hands‑on technical leadership across the full ML lifecycle, including research, model design, experimentation, validation, deployment, and continuous improvement.
• Raise the bar for technical excellence while fostering an inclusive, high‑engagement team culture.
• Oversee the development and productization of ML models addressing real‑world document and biometric challenges at scale.
• Establish and evolve robust MLOps practices to ensure reproducibility, reliability, observability, cost effectiveness, and consistent high‑quality model delivery.
• Ensure the availability, quality, and scalability of labeled data pipelines necessary to support ongoing model development and accuracy improvement.

People & Team Leadership

• Lead, mentor, and develop a team of senior machine learning engineers and technical leaders, fostering a culture of trust, accountability, collaboration, and continuous learning.
• Build high‑performing teams that balance innovation with operational excellence.
• Set clear expectations, provide regular feedback, and support the professional growth and progression of team members.
• Builds trust through transparency, technical credibility, and consistent delivery.

Cross‑Functional Collaboration

• Partner closely with Product Management to define AI/ML roadmaps, prioritize initiatives, and ensure timely and high‑impact delivery.
• Collaborate effectively with Engineering, Architecture, Data, Platform, Security, Legal, and Compliance teams to ensure ML systems are scalable, secure, and…