Machine Learning Engineer

About The Company
LexisNexis Legal & Professional is a global leader in providing legal, regulatory, and business information and analytics solutions. Serving clients in more than 150 countries, the company employs over 11,800 professionals dedicated to delivering innovative tools that enhance productivity and decision-making. As part of RELX, a multinational information and analytics company, LexisNexis leverages cutting-edge technology and data-driven insights to transform the legal industry. The organization is committed to deploying ethical, responsible AI solutions, integrating advanced generative AI and machine learning models to streamline legal research, analysis, and workflow automation. With a focus on innovation, LexisNexis continuously invests in its technological capabilities, employing a talented team of data scientists, engineers, and legal experts to develop scalable, secure, and compliant solutions that meet the evolving needs of its global customer base.
About The Role
Are you passionate about developing scalable AI/ML systems and leading high-performing engineering teams? LexisNexis is seeking a talented Machine Learning Engineer Lead to spearhead the design, development, and deployment of next-generation legal research and analytics platforms. This role requires a blend of deep technical expertise in machine learning and systems engineering, along with leadership skills to guide a team of 4-5 ML engineers. As a key contributor, you will drive platform-level decisions, establish best practices, and ensure the delivery of enterprise-grade solutions that are reliable, scalable, and aligned with responsible AI principles.
The ideal candidate will have hands-on experience in building distributed systems, deploying machine learning models into production, and architecting complex AI frameworks. You will collaborate closely with cross-functional teams to define technical roadmaps, standardize infrastructure patterns, and implement safety and traceability mechanisms. Your leadership will be instrumental in shaping the future of legal analytics products, ensuring they meet rigorous standards for performance, compliance, and ethical AI deployment.
Qualifications
8-10 years of experience in Machine Learning and Software Engineering, with a proven track record of building and deploying large-scale AI systems.
2-3 years of experience in people management, leading and mentoring engineering teams.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field; advanced degrees are preferred.
Strong background in software development, system design, and architecture, with experience in handling large volumes of unstructured data.
Hands-on experience with deploying machine learning models to production environments and managing end-to-end ML lifecycle.
Familiarity with distributed systems, cloud infrastructure, and scalable AI platform development.
Excellent communication and leadership skills, with the ability to influence technical decisions and mentor team members.
Responsibilities
Lead, mentor, and develop a team of 4-5 machine learning engineers, fostering a collaborative and innovative team environment.
Provide architectural guidance and code-level oversight to ensure high-quality, scalable solutions.
Establish and promote best practices for ML system design, testing, deployment, and maintenance.
Conduct design reviews, performance evaluations, and contribute to technical roadmap planning.
Design and architect distributed machine learning systems to support multiple global products and services.
Standardize infrastructure patterns for large language model (LLM) serving and retrieval systems to ensure consistency and efficiency.
Define and implement enterprise-ready agentic frameworks capable of multi-step reasoning and autonomous decision-making.
Lead decisions on deterministic workflows versus autonomous agents, balancing reliability and innovation.
Implement safety guardrails, traceability, and safety layers to ensure responsible AI deployment.
Develop evaluation frameworks to measure reasoning quality, hallucination rates, and system reliability.
Establish and maintain CI/CD standards for the entire ML lifecycle, ensuring continuous integration and deployment.
Ensure compliance with enterprise data governance policies and responsible AI standards, maintaining ethical and legal standards.
Benefits
LexisNexis offers a comprehensive benefits package tailored to support the well-being and professional growth of its employees. These benefits include competitive salary packages, health insurance, retirement plans, paid time off, and wellness programs. The company also provides opportunities for continuous learning and development, including training programs, certifications, and participation in industry conferences. Employees are encouraged to work in a collaborative environment that fosters innovation and recognizes achievement. Additionally, the company offers flexible work arrangements where applicable, along with support for work-life balance to promote long-term career satisfaction and personal well-being.
Equal Opportunity
LexisNexis is an equal opportunity employer committed to fostering an inclusive workplace. The company considers all qualified applicants without regard to race, color, religion, sex, national origin, citizenship, disability, veteran status, age, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. LexisNexis values diversity and is dedicated to creating an environment where all employees can thrive and contribute their unique perspectives. The organization also ensures a fair and accessible hiring process, accommodating applicants with disabilities or other needs upon request. For more information, please review our Candidate Privacy Policy and learn how we protect your data and privacy during the application process.

Work arrangement
Yes