Director of Machine Learning (3966)

GBG

About The Position

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 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.

Requirements

PhD in AI, Machine Learning, Computer Science, or a related field, or equivalent depth of industry experience.
Deep technical expertise in machine learning, computer vision, and deep learning applied to real‑world, production systems.
10+ years of hands‑on experience in machine learning and computer vision, with a substantial portion in leadership roles.
Significant experience leading and scaling machine learning teams in a product‑focused environment.
Proven track record of delivering ML solutions end‑to‑end, from concept through production and ongoing optimization.
Strong experience building and operating MLOps pipelines, data workflows, and production ML systems.
Demonstrated ability to influence across organizational boundaries and communicate effectively with both technical and non‑technical stakeholders.
Experience operating in highly dynamic, fast‑moving environments with competing priorities.

Nice To Haves

Experience with regulated environments, AI governance frameworks, or compliance‑driven ML development would be beneficial
Experience delivering ML solutions with measurable customer or business impact at scale

Responsibilities

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.
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.
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.
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 compliant.
Represent Documents & Biometrics in cross‑company forums related to AI strategy, governance, and innovation.
Ensure that machine learning systems are developed and operated in accordance with applicable AI governance frameworks, regulatory requirements, and ethical best practices.
Contribute to company‑wide AI governance efforts, including AI risk assessment, documentation, explainability, and stakeholder readiness.
Promote appropriate AI literacy within the team and ensure responsible design and use of ML technologies.
Manage multiple complex initiatives simultaneously, balancing innovation, delivery commitments, and operational stability.
Ensure adherence to industry best practices, architectural standards, and engineering quality bars.
Maintain high levels of team morale, engagement, and delivery velocity.