Senior Machine Learning Engineer (3967)

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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 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. 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 production‑grade systems. This role combines strong hands‑on technical execution with mentorship, collaboration, and data‑driven problem solving. Operating within an Agile environment, the Senior ML Engineer works closely with the machine learning team and cross‑functional 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 state‑of‑the‑art machine learning and computer vision models to enhance product capabilities. Research, evaluate, and apply modern architectures and techniques, including CNNs, transformers, and vision‑language models. Implement and benchmark newly developed algorithms on large‑scale datasets, validating both accuracy and throughput. Fine‑tune large‑scale 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, ROC‑AUC, confusion matrices). Analyze training, test, and production data using statistical and visual techniques to identify performance gaps and reliability risks. Propose and implement data‑driven enhancements to model accuracy, robustness, and system stability. Production Deployment MLOps Support end‑to‑end 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 knowledge‑sharing initiatives to raise overall team capability. Contribute actively to Agile ceremonies and collaborative problem‑solving 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 high‑impact ML solutions. Maintain awareness of emerging ML and comput

关于GBG 为各地真实的人赋能安全且有回报的数字生活 我们的使命是确保更多真实的人能够通过数字方式获得机会，并让企业能够接触到更多真实的人。我们的技术利用多样且可靠的数据，为身份和地址验证创建单一事实来源。凭借30多年的经验，我们的团队和技术专注于为每个人赋能安全且有回报的数字生活。无论年龄、地点或背景如何，各地的真实的人都应该能够以数字方式证明他们是谁以及他们住在哪里。 关于团队和职位 CVML团队 作为GBG Documents and Biometrics产品组合的核心，我们的团队专注于创建独特而强大的AI模型。这些模型旨在为我们的客户革新KYC验证。我们推动这些前沿技术的发展，目标是提供无与伦比的文档验证和数字信任解决方案。协作是我们的基石，因为我们汇聚多元专业知识以实现共同成功。在敏捷方法论的指导下，我们的日常运营专注于通过自动化提升效率。 高级机器学习工程师 高级机器学习工程师是一名高级个人贡献者，负责设计、开发、部署并持续改进为生产级系统提供支持的机器学习和计算机视觉模型。该职位将强大的 hands-on 技术执行与指导、协作和数据驱动的问题解决相结合。在敏捷环境中工作，高级ML工程师与机器学习团队及跨职能合作伙伴紧密合作，将产品需求转化为稳健的ML解决方案。该职位要求在现代ML和计算机视觉技术方面具备深厚专业知识，拥有在生产环境中运行模型的经验，并具备指导初级工程师完成完整ML生命周期的能力，同时推动模型性能和产品质量的可衡量改进。 你将做什么 技术开发与创新 设计、实现并优化最先进的机器学习和计算机视觉模型，以增强产品能力。 研究、评估并应用现代架构和技术，包括CNN、transformers和视觉语言模型。 在大规模数据集上实现并基准测试新开发的算法，验证准确性和吞吐量。 使用LoRA和QLoRA等高效适配技术微调大规模模型。 模型评估与数据分析 定义、实现并监控适当的评估指标（例如precision、recall、ROC-AUC、confusion matrices）。 使用统计和可视化技术分析训练、测试和生产数据，以识别性能差距和可靠性风险。 提出并实施数据驱动的增强方案，以提升模型准确性、稳健性和系统稳定性。 生产部署与MLOps 支持端到端ML工作流，包括数据准备、训练、部署、监控和迭代改进。 为CI/CD流水线和生产监控做出贡献，以确保可靠、可复现且可扩展的模型交付。 协助诊断并解决模型性能回退和生产问题。 指导与团队贡献 在ML项目的各个阶段指导和支持初级CVML工程师，包括规划、数据收集、标注、训练、部署和迭代。 参与设计评审、技术讨论和知识分享活动，以提升团队整体能力。 积极参与敏捷仪式和协作式问题解决工作。 持续改进与协作 主动提出对现有模型、工作流、工具和产品功能的改进建议。 与工程、产品和数据相关方有效协作，以交付高影响力的ML解决方案。 保持对新兴ML和计算

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