Do you love collaborating with teams to solve complex technical problems?We are looking for a back-end Machine Learning Engineer Lead in Shanghai China. Are you the one? About the Team Our Machine Learning Engineer Lead partners with multiple technical functions to help improve the performance of our products. We offer advice and support on all matters relating to the attraction, development, retention, engagement and management of our workforce. About the Role We are seeking a Machine Learning Engineer Lead to drive the design, development, deployment, and scaling of machine learning and AI solutions across LexisNexis products and platforms. This role combines technical leadership, architectural ownership, and hands-on development to deliver production-grade ML systems that power legal research, risk analytics, fraud detection, compliance intelligence, and enterprise AI solutions. Responsibilities Technical Leadership & Architecture \\+ Lead the architecture and implementation of scalable AI services using Python-based ecosystems. \\+ Define engineering standards, code quality frameworks, and ML system design best practices. \\+ Review and guide system design decisions across data, model, and service layers. \\+ Drive technical roadmap alignment with enterprise AI strategy. Python Engineering Excellence \\+ Write production-quality Python code with a strong focus on performance, testability, and maintainability. \\+ Design modular, reusable ML components and shared libraries. \\+ Implement robust API services (FastAPI, Flask) for model serving. \\+ Apply advanced Python concepts (async programming, multiprocessing, type hinting, packaging, dependency management). \\+ Enforce unit testing, integration testing, and CI/CD best practices. Machine Learning & AI Development \\+ Develop and deploy models for NLP, classification, ranking, anomaly detection, entity resolution, and generative AI use cases. \\+ Build and optimize LLM-powered systems (RAG pipelines, embeddings, fine-tuning). \\+ Collaborate with data scientists to productionize research models. \\+ Implement feature engineering pipelines and model evaluation frameworks. Cross-Functional Collaboration \\+ Partner with Product, Legal domain experts, Data Engineering, and DevOps teams. \\+ Translate complex business requirements into scalable AI engineering solutions. \\+ Mentor ML engineers and promote a culture of high engineering standards. Requirements: \\+ Bachelors or Masters degree in Computer Science, Engineering, Mathematics, Artificial Intelligence, or a related technical field. \\+ 8+ years of professional experience in software engineering with significant hands-on experience in machine learning system development. \\+ 3+ years of advanced Python development experience in production-grade environments. \\+ Strong technical expertise in: \\+ Python programming, including object-oriented design, asynchronous programming, dependency management, and modern testing frameworks, etc. \\+ Faimiliar with Machine learning frameworks such as PyTorch, TensorFlow, and Scikit-learn. \\+ Building and deploying model-serving APIs using FastAPI or Flask. \\+ Proven experience deploying and maintaining AI models in large-scale, production environments. \\+ Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. \\+ Solid experience implementing CI/CD pipelines and applying DevOps best practices. \\+ Practical experience with containerization (Docker) and container orchestration (Kubernetes). \\+ Strong understanding of distributed systems, scalable data pipelines, and service-oriented architectures. \\+ Strong written and verbal communication skills in English, with the ability to effectively collaborate across global teams. Work in a way that works for you We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. Working for you: We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: Medical and Life Insurance: Coverage for Medical and life risk. Long-Service Award: Recognition for loyalty and dedication. Marriage and New Baby Gifts: Celebratory tokens for special life events. Festivals and Birthday Gifts: Spreading joy on occasions that matter. Annual Medical Check-up: Prioritizing employee well-being through regular health check-ups. Flexible Benefits via CIIC Platform: Personalized benefits accessible through a user-friendly platform. Paid Time Off: Annual Leave, Flex Family Care Leave, Birthday Leave, Marriage Leave, Compassionate Leave, Medical and Hospitalization Leave, Examination Leave Gazetted Public Holiday Family Care leave (Maternity/Paternity Leave and Adoption Leave) About the Business LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here () to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate . We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights. RELX is a global provider of information-based analytics and decision tools for professional and business customers, enabling them to make better decisions, get better results and be more productive. Our purpose is to benefit society by developing products that help researchers advance scientific knowledge; doctors and nurses improve the lives of patients; lawyers promote the rule of law and achieve justice and fair results for their clients; businesses and governments prevent fraud; consumers access financial services and get fair prices on insurance; and customers learn about markets and complete transactions. Our purpose guides our actions beyond the products that we develop. It defines us as a company. Every day across RELX our employees are inspired to undertake initiatives that make unique contributions to society and the communities in which we operate.

The role requires a Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Artificial Intelligence, or a related technical field. Candidates need over 8 years of professional software engineering experience with significant hands-on machine learning system development. Additionally, 3+ years of advanced Python development experience in production environments is necessary. Strong technical expertise in Python programming, including object-oriented design, asynchronous programming, dependency management, and modern testing frameworks, is essential. Familiarity with machine learning frameworks like PyTorch, TensorFlow, and Scikit-learn is required, as is experience building and deploying model-serving APIs using FastAPI or Flask. Proven experience deploying and maintaining AI models in large-scale, production environments, hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and solid experience implementing CI/CD pipelines and applying DevOps best practices are also necessary. Practical experience with containerization (Docker) and container orchestration (Kubernetes), along with a strong understanding of distributed systems, scalable data pipelines, and service-oriented architectures, are required. Strong written and verbal communication skills in English are also a requirement.