Director of Machine Learning
GBG Plc
full-time
Posted on:
Location Type: Remote
Location: United States
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Job Level
About the role
- 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.
- 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.
- 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.
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.
- 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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningcomputer visiondeep learningMLOpsdata workflowsmodel designmodel validationmodel deploymentAI governancefraud detection
Soft Skills
leadershipmentoringcollaborationcommunicationteam buildingtrustaccountabilitycontinuous learningfeedbackengagement
Certifications
PhD in AIPhD in Machine LearningPhD in Computer Science